@Test public void testFCdf() { logger.info("FCdf"); double x = 3.0; int f1 = 10; int f2 = 2; double expResult = 0.7241964339413; double result = ContinuousDistributions.fCdf(x, f1, f2); assertEquals(expResult, result, Constants.DOUBLE_ACCURACY_HIGH); }
public static double fCdf(double x, int f1, int f2) { if(x<0 || f1<=0 || f2<=0) { throw new IllegalArgumentException("All the parameters must be positive."); } double Z = x/(x + (double)f2/f1); double FCdf = betaCdf(Z,f1/2.0,f2/2.0); return FCdf; }
ContinuousDistributions { public static double fCdf(double x, int f1, int f2) { if(x<0 || f1<=0 || f2<=0) { throw new IllegalArgumentException("All the parameters must be positive."); } double Z = x/(x + (double)f2/f1); double FCdf = betaCdf(Z,f1/2.0,f2/2.0); return FCdf; } }
ContinuousDistributions { public static double fCdf(double x, int f1, int f2) { if(x<0 || f1<=0 || f2<=0) { throw new IllegalArgumentException("All the parameters must be positive."); } double Z = x/(x + (double)f2/f1); double FCdf = betaCdf(Z,f1/2.0,f2/2.0); return FCdf; }  }
ContinuousDistributions { public static double fCdf(double x, int f1, int f2) { if(x<0 || f1<=0 || f2<=0) { throw new IllegalArgumentException("All the parameters must be positive."); } double Z = x/(x + (double)f2/f1); double FCdf = betaCdf(Z,f1/2.0,f2/2.0); return FCdf; }  static double chisquareCdf(double x, int df); static double gaussCdf(double z); static double gamma(double x); static double logGamma(double Z); static double studentsCdf(double x, int df); static double exponentialCdf(double x, double lamda); static double betaCdf(double x, double a, double b); static double fCdf(double x, int f1, int f2); static double gammaCdf(double x, double a, double b); static double uniformCdf(double x, double a, double b); static double kolmogorov(double z); static double gaussInverseCdf(double p); static double chisquareInverseCdf(double p, int df); static double normalQuantile(double p, double mu, double sigma); static double dirichletPdf(double[] pi, double[] ai); static double dirichletPdf(double[] pi, double a); static double[] multinomialGaussianSample(double[] mean, double[][] covariance); static double multinomialGaussianPdf(double[] mean, double[][] covariance, double[] x); }
ContinuousDistributions { public static double fCdf(double x, int f1, int f2) { if(x<0 || f1<=0 || f2<=0) { throw new IllegalArgumentException("All the parameters must be positive."); } double Z = x/(x + (double)f2/f1); double FCdf = betaCdf(Z,f1/2.0,f2/2.0); return FCdf; }  static double chisquareCdf(double x, int df); static double gaussCdf(double z); static double gamma(double x); static double logGamma(double Z); static double studentsCdf(double x, int df); static double exponentialCdf(double x, double lamda); static double betaCdf(double x, double a, double b); static double fCdf(double x, int f1, int f2); static double gammaCdf(double x, double a, double b); static double uniformCdf(double x, double a, double b); static double kolmogorov(double z); static double gaussInverseCdf(double p); static double chisquareInverseCdf(double p, int df); static double normalQuantile(double p, double mu, double sigma); static double dirichletPdf(double[] pi, double[] ai); static double dirichletPdf(double[] pi, double a); static double[] multinomialGaussianSample(double[] mean, double[][] covariance); static double multinomialGaussianPdf(double[] mean, double[][] covariance, double[] x);  }