Displaying similar documents to “Testing for normality”

Some aspects of the conditional inference when the sample size is random.

A.K.P.C. Swain (1983)

Trabajos de Estadística e Investigación Operativa

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The conditional test is compared with other relevant test procedures for testing parameters of Normal and Exponential populations. It is seen that under certain conditions the conditional test is more powerful than the relevant unconditional tests. An example is provided where the conditional test given the ancillary is uniformaly more powerful than the obvious unconditional test.

Normalization of the Kolmogorov–Smirnov and Shapiro–Wilk tests of normality

Zofia Hanusz, Joanna Tarasińska (2015)

Biometrical Letters

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Two very well-known tests for normality, the Kolmogorov-Smirnov and the Shapiro- Wilk tests, are considered. Both of them may be normalized using Johnson’s (1949) SB distribution. In this paper, functions for normalizing constants, dependent on the sample size, are given. These functions eliminate the need to use non-standard statistical tables with normalizing constants, and make it easy to obtain p-values for testing normality.

The behavior of locally most powerful tests

Marek Omelka (2005)

Kybernetika

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The locally most powerful (LMP) tests of the hypothesis H : θ = θ 0 against one-sided as well as two-sided alternatives are compared with several competitive tests, as the likelihood ratio tests, the Wald-type tests and the Rao score tests, for several distribution shapes and for location, shape and vector parameters. A simulation study confirms the importance of the condition of local unbiasedness of the test, and shows that the LMP test can sometimes dominate the other tests only in a very restricted...