论文信息 - The Kolmogorov-Smirnov Test for Goodness of Fit

The Kolmogorov-Smirnov Test for Goodness of Fit

Abstract The test is based on the maximum difference between an empirical and a hypothetical cumulative distribution. Percentage points are tabled, and a lower bound to the power function is charted. Confidence limits for a cumulative distribution are described. Examples are given. Indications that the test is superior to the chi-square test are cited.

F. Massey

[1] J. Wolfowitz,et al. Confidence Limits for Continuous Distribution Functions , 1939 .

[2] A. Wald,et al. On the Choice of the Number of Class Intervals in the Application of the Chi Square Test , 1942 .

[3] Henry Scheffe,et al. Statistical Inference in the Non-Parametric Case , 1943 .

[4] W. Feller. On the Kolmogorov–Smirnov Limit Theorems for Empirical Distributions , 1948 .

[5] N. Smirnov. Table for Estimating the Goodness of Fit of Empirical Distributions , 1948 .

[6] J. Doob. Heuristic Approach to the Kolmogorov-Smirnov Theorems , 1949 .

[7] N. Metropolis,et al. The Monte Carlo method. , 1949 .

[8] J. Wolfowitz,et al. Non-parametric Statistical Inference , 1949 .

[9] C. Williams,et al. The Choice of the Number and Width of Classes for the Chi-Square Test of Goodness of Fit , 1950 .

[10] F. Massey,et al. A Note on the Estimation of a Distribution Function by Confidence Limits , 1950 .

[11] F. Massey,et al. A Note on the Power of a Non-Parametric Test , 1950 .