LUMEN 发表于 2025-3-25 03:52:04

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无思维能力 发表于 2025-3-25 09:20:33

Book 2010istician who is involved in comparative studies....The book gives a self-contained theoretical treatment of a wide range of goodness-of-fit methods, including graphical methods, hypothesis tests, model selection and density estimation. It relies on parametric, semiparametric and nonparametric theory

小卒 发表于 2025-3-25 13:55:47

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倾听 发表于 2025-3-25 19:45:57

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档案 发表于 2025-3-25 20:45:14

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nuclear-tests 发表于 2025-3-26 03:58:26

Smooth Testsved some optimality properties. Although smooth tests are considered as nonparametric tests, they are actually constructed by first considering a .-dimensional .in which the hypothesised distribution is embedded. These smooth alternatives are the subject of Section 4.1. The tests are given in Sectio

听觉 发表于 2025-3-26 07:18:16

Methods Based on the Empirical Distribution Functione old tests, as the Kolmogorov-Smirnov test, but also in recent years new tests have still been added to this class. A discussion on the EDF and empirical processes has been given in Sections 2.1 and 2.2. Sections 5.1 and 5.2 are devoted to the Kolmogorov-Smirnov and the Cramér-von Mises type tests,

Virtues 发表于 2025-3-26 09:52:38

Introductionre the distribution of the sample observations with a hypothesised distribution, we are now concerned with comparing the distributions of two or more populations from which we have observations at our disposal. As both classes of problems are about comparing distributions, many of the methods develo

正常 发表于 2025-3-26 16:10:58

Preliminaries (Building Blocks)esumes that the null hypothesis specifies some parameterised parametric distribution. On the other hand, most two-sample tests can be based on an asymptotic null distribution that can be derived from a central limit theorem, or from the application of the continuous mapping theorem and the weak conv

dilute 发表于 2025-3-26 17:58:20

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查看完整版本: Titlebook: Comparing Distributions; Olivier Thas Book 2010 Springer-Verlag New York 2010 data analysis.goodness-of-fit tests.graphical methods.nonpar