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| 柯尔莫哥洛夫-斯米尔诺夫检验× | 双样本柯尔莫哥洛夫-斯米尔诺夫检验× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族≠ | Hypothesis test | Regression model |
| 起源年份≠ | 1933 | 1948 |
| 提出者≠ | Andrey Nikolaevich Kolmogorov; Nikolai Vasilyevich Smirnov | N. V. Smirnov |
| 类型≠ | Nonparametric goodness-of-fit test | Nonparametric two-sample distribution test |
| 开创性文献≠ | Kolmogorov, A. N. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83–91. link ↗ | Smirnov, N. V. (1948). Table for Estimating the Goodness of Fit of Empirical Distributions. Annals of Mathematical Statistics, 19(2), 279-281. DOI ↗ |
| 别名≠ | KS test, K-S test, one-sample KS test, Kolmogorov-Smirnov Testi | KS two-sample test, two-sample KS test, İki Örneklem Kolmogorov-Smirnov Testi |
| 相关≠ | 2 | 3 |
| 摘要≠ | The Kolmogorov-Smirnov (KS) test is a nonparametric goodness-of-fit test that assesses whether a sample comes from a specified theoretical distribution, such as the normal or exponential. First formalised by Andrey Kolmogorov in 1933 and further developed by Nikolai Smirnov in 1948, it compares the empirical cumulative distribution function of the observed data against a target theoretical CDF and quantifies their maximum absolute deviation. | The two-sample Kolmogorov-Smirnov test is a nonparametric procedure that asks whether two independent groups are drawn from the same continuous distribution. Building on Smirnov's 1948 tables, it compares the empirical cumulative distribution functions (CDFs) of the two samples and uses their maximum absolute distance as the test statistic. |
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