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dBellB<-function (x, a, b, k, lambda, log = FALSE)
{
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellB.R
|
dBellBX<-function (x, a,lambda, log = FALSE)
{
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellBX.R
|
dBellE<-function (x, alpha,lambda, log = FALSE)
{
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellE.R
|
dBellEE<-function (x, alpha,beta,lambda, log = FALSE)
{
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellEE.R
|
dBellEW<-function (x, alpha, beta, theta, lambda, log = FALSE)
{
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellEW.R
|
dBellF<-function (x, a, b, lambda, log = FALSE)
{
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellF.R
|
dBellL<-function (x, b, q, lambda, log = FALSE)
{
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellL.R
|
dBellW<-function (x, alpha,beta,lambda, log = FALSE)
{
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dBellW.R
|
dCBellB<-function (x, a, b, k, lambda, log = FALSE)
{
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellB.R
|
dCBellE<-function (x, alpha,lambda, log = FALSE)
{
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellE.R
|
dCBellEE<-function (x, alpha,beta,lambda, log = FALSE)
{
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellEE.R
|
dCBellEW<-function (x, alpha,beta,theta,lambda, log = FALSE)
{
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellEW.R
|
dCBellF<-function (x, a, b, lambda, log = FALSE)
{
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellF.R
|
dCBellL<-function (x, b, q, lambda, log = FALSE)
{
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellL.R
|
dCBellW<-function (x, alpha,beta,lambda, log = FALSE)
{
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dCBellW.R
|
dCBellBX<-function (x, a,lambda, log = FALSE)
{
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
return(pdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/dcBellBX.R
|
hBellB<-function (x, a, b, k, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellB.R
|
hBellBX<-function (x, a,lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellBX.R
|
hBellE<-function (x, alpha,lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellE.R
|
hBellEE<-function (x, alpha, beta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellEE.R
|
hBellEW<-function (x, alpha, beta, theta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellEW.R
|
hBellF<-function (x, a, b, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellF.R
|
hBellL<-function (x, b, q, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellL.R
|
hBellW<-function (x, alpha, beta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
pdf <- x
pdf[log == FALSE] <-lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
pdf[log == TRUE] <-log(lambda)+log(g)+(lambda*(1-G))-exp(lambda)*(1-exp(-lambda*G))-log((1-(exp(-exp(lambda)+1))))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hBellW.R
|
hCBellB<-function (x, a, b, k, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellB.R
|
hCBellBX<-function (x, a,lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellBX.R
|
hCBellE<-function (x, alpha,lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellE.R
|
hCBellEE<-function (x, alpha, beta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellEE.R
|
hCBellEW<-function (x, alpha, beta, theta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellEW.R
|
hCBellF<-function (x, a, b, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellF.R
|
hCBellL<-function (x, b, q, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellL.R
|
hCBellW<-function (x, alpha, beta, lambda, log = FALSE,log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
pdf <- x
pdf[log == FALSE] <- lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
pdf[log == TRUE] <- log(lambda)+log(g)+(lambda*G)+(exp(lambda*G)-1)-log((exp(exp(lambda)-1)-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
hrf<-pdf/(1-cdf)
return(hrf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/hCBellW.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellB<-function (x, a, b, k, lambda, method="B")
{
pdf_BellB<-function(par,x){
a=par[1]
b=par[2]
k=par[3]
lambda=par[4]
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellB<-function(par,x){
a=par[1]
b=par[2]
k=par[3]
lambda=par[4]
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellB, cdf = cdf_BellB, starts = c(a, b, k, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellB.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellBX<-function (x, a,lambda, method="B")
{
pdf_BellBX<-function(par,x){
a=par[1]
lambda=par[2]
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellBX<-function(par,x){
a=par[1]
lambda=par[2]
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellBX, cdf = cdf_BellBX, starts = c(a,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellBX.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellE<-function (x, alpha,lambda, method="B")
{
pdf_BellE<-function(par,x){
alpha=par[1]
lambda=par[2]
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellE<-function(par,x){
alpha=par[1]
lambda=par[2]
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellE, cdf = cdf_BellE, starts = c(alpha,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellE.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellEE<-function (x, alpha, beta, lambda, method="B")
{
pdf_BellEE<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellEE<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellEE, cdf = cdf_BellEE, starts = c(alpha,beta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellEE.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellEW<-function (x, alpha, beta, theta, lambda, method="B")
{
pdf_BellEW<-function(par,x){
alpha=par[1]
beta=par[2]
theta=par[3]
lambda=par[4]
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellEW<-function(par,x){
alpha=par[1]
beta=par[2]
theta=par[3]
lambda=par[4]
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellEW, cdf = cdf_BellEW, starts = c(alpha,beta,theta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellEW.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellF<-function (x, a, b, lambda, method="B")
{
pdf_BellF<-function(par,x){
a=par[1]
b=par[2]
lambda=par[3]
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellF<-function(par,x){
a=par[1]
b=par[2]
lambda=par[3]
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellF, cdf = cdf_BellF, starts = c(a, b, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellF.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellL<-function (x, b, q, lambda, method="B")
{
pdf_BellL<-function(par,x){
b=par[1]
q=par[2]
lambda=par[3]
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellL<-function(par,x){
b=par[1]
q=par[2]
lambda=par[3]
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellL, cdf = cdf_BellL, starts = c(b, q, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellL.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mBellW<-function (x, alpha, beta, lambda, method="B")
{
pdf_BellW<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_BellW<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_BellW, cdf = cdf_BellW, starts = c(alpha,beta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mBellW.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellB<-function (x, a, b, k, lambda, method="B")
{
pdf_CBellB<-function(par,x){
a=par[1]
b=par[2]
k=par[3]
lambda=par[4]
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellB<-function(par,x){
a=par[1]
b=par[2]
k=par[3]
lambda=par[4]
G=(1-((1+(x/a)^b))^(-k))
g=k*((1+(x/a)^b))^(-k-1) *b*x^(b-1)*a^(-b)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellB, cdf = cdf_CBellB, starts = c(a, b, k, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellB.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellBX<-function (x, a,lambda, method="B")
{
pdf_CBellBX<-function(par,x){
a=par[1]
lambda=par[2]
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(f)
}
cdf_CBellBX<-function(par,x){
a=par[1]
lambda=par[2]
G=(1-exp(-x^2))^a
g=2*a*x*exp(-x^2)*(1-exp(-x^2))^(a-1)
F=(1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
f=lambda*g*exp(lambda*(1-G))*exp(-exp(lambda)*(1-exp(-lambda*G)))/(1-(exp(-exp(lambda)+1)))
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellBX, cdf = cdf_CBellBX, starts = c(a,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellBX.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellE<-function (x, alpha,lambda, method="B")
{
pdf_CBellE<-function(par,x){
alpha=par[1]
lambda=par[2]
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellE<-function(par,x){
alpha=par[1]
lambda=par[2]
G=(1-exp(-alpha*x))
g=alpha*exp(-alpha*x)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellE, cdf = cdf_CBellE, starts = c(alpha,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellE.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellEE<-function (x, alpha, beta, lambda, method="B")
{
pdf_CBellEE<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellEE<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x))^beta
g=alpha*exp(-alpha*x)*beta*(1-exp(-alpha*x))^(beta-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellEE, cdf = cdf_CBellEE, starts = c(alpha,beta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellEE.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellEW<-function (x, alpha, beta, theta, lambda, method="B")
{
pdf_CBellEW<-function(par,x){
alpha=par[1]
beta=par[2]
theta=par[3]
lambda=par[4]
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellEW<-function(par,x){
alpha=par[1]
beta=par[2]
theta=par[3]
lambda=par[4]
G=(1-exp(-alpha*x^(beta)))^theta
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)*theta*(1-exp(-alpha*x^(beta)))^(theta-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellEW, cdf = cdf_CBellEW, starts = c(alpha,beta,theta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellEW.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellF<-function (x, a, b, lambda, method="B")
{
pdf_CBellF<-function(par,x){
a=par[1]
b=par[2]
lambda=par[3]
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellF<-function(par,x){
a=par[1]
b=par[2]
lambda=par[3]
G=(1-((1+(x/a)^b))^(-1))
g=((1+(x/a)^b))^(-2) *b*x^(b-1)*a^(-b)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellF, cdf = cdf_CBellF, starts = c(a, b, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellF.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellL<-function (x, b, q, lambda, method="B")
{
pdf_CBellL<-function(par,x){
b=par[1]
q=par[2]
lambda=par[3]
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellL<-function(par,x){
b=par[1]
q=par[2]
lambda=par[3]
G=(1-((1+(x/b)))^(-q))
g=(q/b)*(1+(x/b))^(-q-1)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellL, cdf = cdf_CBellL, starts = c(b, q, lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellL.R
|
#' @export
#' @import AdequacyModel
#' @import graphics
mCBellW<-function (x, alpha, beta, lambda, method="B")
{
pdf_CBellW<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(f)
}
cdf_CBellW<-function(par,x){
alpha=par[1]
beta=par[2]
lambda=par[3]
G=(1-exp(-alpha*x^beta))
g=alpha*beta*x^(beta-1)*exp(-alpha*x^beta)
F=(exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
f=lambda*g*exp(lambda*G)*exp(exp(lambda*G)-1)/(exp(exp(lambda)-1)-1)
return(F)
}
res = suppressWarnings(AdequacyModel::goodness.fit(pdf = pdf_CBellW, cdf = cdf_CBellW, starts = c(alpha,beta,lambda), data = x, method = method, mle = NULL))
aux = cbind(res$mle, res$Erro)
colnames(aux) = c("MLE", "SE")
aux1 = cbind(res$AIC, res$BIC, res$W,res$A, res$Value)
colnames(aux1) = c("AIC", "BIC", "W", "A","-2L")
rownames(aux1) = c("")
aux2 = cbind(res$KS$statistic, res$KS$p.value)
colnames(aux2) = c("KS Statistic", "KS p-value")
rownames(aux2) = c("")
aux3 = cbind(if (res$Convergence == 0) {
"Converged"
}
else {
"Not Converged"
})
colnames(aux3) = c("")
rownames(aux3) = c("")
list(Estimates = aux, `Goodness-of-Fit Tests` = aux1, `Kolmogorov-Smirnov Test` = aux2,
`Convergence Status` = aux3)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/mCBellW.R
|
pBellB<-function (x, a, b, k, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-k))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellB.R
|
pBellBX<-function (x, a,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-x^2))^a
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellBX.R
|
pBellE<-function (x, alpha,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellE.R
|
pBellEE<-function (x, alpha,beta,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))^beta
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellEE.R
|
pBellEW<-function (x, alpha, beta, theta, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^(beta)))^theta
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellEW.R
|
pBellF<-function (x, a, b, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellF.R
|
pBellL<-function (x, b, q, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/b)))^(-q))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellL.R
|
pBellW<-function (x, alpha,beta,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^beta))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pBellW.R
|
pCBellB<-function (x, a, b, k, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-k))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellB.R
|
pCBellBX<-function (x, a,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-x^2))^a
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellBX.R
|
pCBellE<-function (x, alpha,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellE.R
|
pCBellEE<-function (x, alpha,beta,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))^beta
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellEE.R
|
pCBellEW<-function (x, alpha,beta,theta,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^(beta)))^theta
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellEW.R
|
pCBellF<-function (x, a, b, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-1))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellF.R
|
pCBellL<-function (x, b, q, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/b)))^(-q))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellL.R
|
pCBellW<-function (x, alpha,beta,lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x^beta))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (exp(exp(lambda*G)-1)-1)/(exp(exp(lambda)-1)-1)
cdf[log.p == TRUE & lower.tail == TRUE] <- log(exp(exp(lambda*G)-1)-1)-log(exp(exp(lambda)-1)-1)
cdf[log.p == FALSE & lower.tail == FALSE] <- (exp(exp(lambda)-1)-exp(exp(lambda*G)-1))/((exp(exp(lambda)-1)-1))
cdf[log.p == TRUE & lower.tail == FALSE] <- log(exp(exp(lambda)-1)-exp(exp(lambda*G)-1))-log((exp(exp(lambda)-1)-1))
return(cdf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/pCBellW.R
|
qBellB<-function(p, a, b, k, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- a*(((1-t)^(-1/k) -1)^(1/b))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellB.R
|
qBellBX<-function(p,a,lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- (-1*log(1-(t)^(1/a)))^(0.5)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellBX.R
|
qBellE<-function(p,alpha,lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- -1/alpha*log(1-t)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellE.R
|
qBellEE<-function(p,alpha, beta, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- -1/alpha*log(1-(t)^(1/beta))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellEE.R
|
qBellEW<-function(p, alpha, beta, theta, lambda, log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- (-1/alpha*log(1-(t)^(1/theta)))^(beta)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellEW.R
|
qBellF<-function(p, a, b, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- a*(((1-t)^(-1) -1)^(1/b))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellF.R
|
qBellL<-function(p, b, q, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- b*(((1-t)^(-1/q))-1)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellL.R
|
qBellW<-function(p,alpha, beta, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(-1/lambda*log(1-((log(1-(p[p >= 0 & p <= 1])*(1-(exp(-exp(lambda)+1)))))/(-exp(lambda)))))
qf[p >= 0 & p <= 1] <- (-1/alpha*log(1-t))^(beta)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qBellW.R
|
qCBellB<-function(p, a, b, k, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- a*(((1-t)^(-1/k) -1)^(1/b))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellB.R
|
qCBellBX<-function(p,a,lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- (-1*log(1-(t)^(1/a)))^(0.5)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellBX.R
|
qCBellE<-function(p,alpha,lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- -1/alpha*log(1-t)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellE.R
|
qCBellEE<-function(p,alpha, beta, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- -1/alpha*log(1-(t)^(1/beta))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellEE.R
|
qCBellEW<-function(p,alpha, beta, theta, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- (-1/alpha*log(1-(t)^(1/theta)))^(beta)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellEW.R
|
qCBellF<-function(p, a, b, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- a*(((1-t)^(-1) -1)^(1/b))
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellF.R
|
qCBellL<-function(p, b, q, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- b*(((1-t)^(-1/q))-1)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellL.R
|
qCBellW<-function(p,alpha, beta, lambda,log.p = FALSE, lower.tail = TRUE){
if (log.p == TRUE)
p <- exp(p)
if (lower.tail == FALSE)
p <- 1 - p
qf <- rep(NaN, length(p))
t=(1/lambda*log(log(((p[p >= 0 & p <= 1])*(exp(exp(lambda)-1)-1))+1)+1))
qf[p >= 0 & p <= 1] <- (-1/alpha*log(1-t))^(beta)
return(qf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/qCBellW.R
|
#' @import stats
rBellB<-function(n, a, b, k, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellB(p, a, b, k, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellB.R
|
#' @import stats
rBellBX<-function(n, a,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellBX(p, a, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellBX.R
|
#' @import stats
rBellE<-function(n, alpha,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellE(p, alpha, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellE.R
|
#' @import stats
rBellEE<-function(n, alpha,beta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellEE(p, alpha, beta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellEE.R
|
#' @import stats
rBellEW<-function(n, alpha,beta,theta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellEW(p, alpha, beta, theta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellEW.R
|
#' @import stats
rBellF<-function(n, a, b, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellF(p, a, b, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellF.R
|
#' @import stats
rBellL<-function(n, b, q, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellL(p, b, q, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellL.R
|
#' @import stats
rBellW<-function(n, alpha,beta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qBellW(p, alpha, beta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rBellW.R
|
#' @import stats
rCBellB<-function(n, a, b, k, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellB(p, a, b, k, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellB.R
|
#' @import stats
rCBellBX<-function(n, a,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellBX(p, a, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellBX.R
|
#' @import stats
rCBellE<-function(n, alpha,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellE(p, alpha, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellE.R
|
#' @import stats
rCBellEE<-function(n, alpha,beta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellEE(p, alpha, beta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellEE.R
|
#' @import stats
rCBellEW<-function(n, alpha,beta,theta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellEW(p, alpha, beta, theta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellEW.R
|
#' @import stats
rCBellF<-function(n, a, b, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellF(p, a, b, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellF.R
|
#' @import stats
rCBellL<-function(n, b, q, lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellL(p, b, q, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellL.R
|
#' @import stats
rCBellW<-function(n, alpha,beta,lambda)
{
p <- runif(n, min = 0, max = 1)
rn <- qCBellW(p, alpha, beta, lambda)
return(rn)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/rCBellW.R
|
sBellB<-function (x, a, b, k, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-((1+(x/a)^b))^(-k))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
sf<-1-cdf
return(sf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/sBellB.R
|
sBellBX<-function (x, a, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-x^2))^a
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
sf<-1-cdf
return(sf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/sBellBX.R
|
sBellE<-function (x, alpha, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
sf<-1-cdf
return(sf)
}
|
/scratch/gouwar.j/cran-all/cranData/BGFD/R/sBellE.R
|
sBellEE<-function (x, alpha, beta, lambda , log.p = FALSE, lower.tail = TRUE)
{
G=(1-exp(-alpha*x))^beta
cdf <- x
cdf[log.p == FALSE & lower.tail == TRUE] <- (1-exp(-exp(lambda)*(1-exp(-lambda*G))))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == TRUE] <- log(1-exp(-exp(lambda)*(1-exp(-lambda*G))))-log(1-(exp(-exp(lambda)+1)))
cdf[log.p == FALSE & lower.tail == FALSE] <- ((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))/(1-(exp(-exp(lambda)+1)))
cdf[log.p == TRUE & lower.tail == FALSE] <- log((exp(-exp(lambda)*(1-exp(-lambda*G))))-(exp(-exp(lambda)+1)))-log(1-(exp(-exp(lambda)+1)))
sf<-1-cdf
return(sf)
}
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/scratch/gouwar.j/cran-all/cranData/BGFD/R/sBellEE.R
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