Displaying similar documents to “A course in spatial visualisation.”

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...

Power comparison of Rao′s score test, the Wald test and the likelihood ratio test in (2xc) contingency tables

Anita Dobek, Krzysztof Moliński, Ewa Skotarczak (2015)

Biometrical Letters

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There are several statistics for testing hypotheses concerning the independence of the distributions represented by two rows in contingency tables. The most famous are Rao′s score, the Wald and the likelihood ratio tests. A comparison of the power of these tests indicates the Wald test as the most powerful.

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.

Goodness-of-fit test for long range dependent processes

Gilles Fay, Anne Philippe (2010)

ESAIM: Probability and Statistics

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In this paper, we make use of the information measure introduced by Mokkadem (1997) for building a goodness-of-fit test for long-range dependent processes. Our test statistic is performed in the frequency domain and writes as a non linear functional of the normalized periodogram. We establish the asymptotic distribution of our statistic under the null hypothesis. Under specific alternative hypotheses, we prove that the power converges to one. The performance of our test procedure is illustrated...