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PDF | This paper presents a distribution-free multivariate Kolmogorov-Smirnov goodness-of-fit test. The test uses a statistic which is built using. Kolmogorov-Smirnov g. – Since the underlying test is for testing uniformity of data in (0,1), each theoretical distribution requires its own transformation The Kolmogorov–Smirnov test can be modified to serve as a goodness of fit test. In the special case of testing for normality of the distribution, We already know how to test this hypothesis using chi-squared goodness-of-fit test. If dis tribution P0 is continuous we had to group the data and consider The Kolmogorov-Smirnov Test for Goodness of Fit. Author(s): Frank J. Massey, Jr. Source: Journal of the American Statistical Association, Vol. 46, No.Kolmogorov-Smirnov Goodness-of-Fit Test · Purpose: Test for Distributional Adequacy · Characteristics and Limitations of the K-S Test, An attractive feature of (Kolmogorov-Smirnov one-sample test). Introduction. • A test for goodness of fit usually involves examining a random sample from some unknown distribution probability density function (PDF). The Chi-Square test is based on the PDF. Both, the AD and KS GoF tests, use the cumulative distribution function (CDF)