Self-Validating Computations of Probabilities for Selected Central and Noncentral Univariate Probability Functions
本文报告了基于区间算术的自验证计算方法，用于计算单变量连续分布的概率和百分位数，保证误差有界，涵盖正态、不完全伽马、不完全贝塔和非中心卡方分布。
Abstract Self-validating computation based on interval arithmetic can produce computed values with a guaranteed error bound. Such methods are especially useful whenever the computed results must satisfy given accuracy requirements. This article reports methods for obtaining self-validating results when computing probabilities and percentiles of univariate continuous distributions. Probability functions dealt with explicitly in the article are normal, incomplete gamma, incomplete beta, and noncentral chi-squared.