1. A method of finding statistical bounds for a performance target F of a circuit affected by M independent statistical model parameters (x 1 , x 2 ,. .. , x M ), where M is an integer, said method comprising: determining, by a computer, a nominal value x j0 , a standard deviation σ j , and a probability density function {tilde over (p)}(x j ; x j0 , σ j ) for each parameter x j , where j=1, 2,. .. , M; constructing, by said computer, a joint probability density function {tilde over (P)}(x 1 , x 2 ,. .. , x M ), for all of said M independent statistical model parameters (x 1 , x 2 ,. .. , x M ), where P ~ ⁡ ( x 1 , x 2 , … ⁢ , x M ) = ∏ j = 1 M ⁢ p ~ ⁡ ( x j ; x j ⁢ ⁢ 0 , σ j ) ; and, based on said joint probability density function {tilde over (P)}(x 1 , x 2 ,. .. , x M ), determining, by said computer, said statistical bounds of said performance target F as defined by a symmetric interval from a lower statistical bound −Kσ to an upper statistical bound +Kσ by performing the following: constructing a Kσ equal-probability-density surface S(x 1 , x 2 ,. .. , x M ; K)=0 of said joint probability density function {tilde over (P)}(x 1 , x 2 ,. .. , x M ), and solving a constrained optimization problem on said Kσ equal-probability-density surface S(x 1 , x 2 ,. .. , x M ; K)=0 to determine said lower statistical bound −Kσ and said upper statistical bound +Kσ.