Quantitative analytics techniques: Kolmogorov-Smirnov goodness of fit test for type I censored samples
El-Kafrawy, Passent
El-Kafrawy, Passent
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2026
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Abstract
This chapter provides a detailed and thorough examination of the Kolmogorov-Smirnov goodness-of-fit test, offering a comprehensive overview of its principles and applications. The chapter presents Mathematica codes for the Kolmogorov-Smirnov goodness-of-fit test that are tailored specifically for type I right censored samples from the three most commonly studied probability distributions in reliability studies and life analysis: normal, lognormal, and Weibull. These codes, which are not currently documented in existing literature, offer a unique contribution to the field. Several real-world examples from the literature are provided to illustrate the suitability of experimental life data to candidate probability distributions.
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Mathematical Modeling for Big Data Analytics