AN INTERMEDIATE-PRECISION APPROXIMATION OF THE INVERSE CUMULATIVE NORMAL-DISTRIBUTION

Accurate methods used to evaluate the inverse of the standard normal cumulative distribution function at probability p commonly used today are too cumbersome and/or slow to obtain a large number of evaluations reasonably quickly, e.g., as required in certain Monte Carlo applications. Previously reported simple approximations all have a maximum absolute error epsilon(m) > 10(-4) for a p-range of practical concern, such as Min[p,1-p] greater-than-or-equal-to 10(-6). An 11-term polynomial-based approximation is presented for which epsilon(m) < 10(-6) in this range.