We propose a method based on partial least squares (PLS) regression to estimate the probability density function of the critical path delay. The method works on a reduced problem facilitated by PLS regression and requires only 10 2  samples to achieve satisfactory accuracy. The method is verified by simulations on ISCAS'85 benchmark circuits.
['Yu Ben', 'Costas J. Spanos']
Estimating the probability density function of critical path delay via partial least squares dimension reduction