Using Piecewise Polynomial Approximations to Generate from Arbitrary Continuous Distributions

Approximate inverse cdf algorithms are ideally suited for generating random variates from new and unusual continuous distributions for which exact generators have not yet been constructed. Piecewise polynomials provide a flexible means to approximate the inverse cdf, particularly since increased accuracy is obtained simply by increasing the order of the polynomials.