Results 251 to 260 of about 848,819 (301)

Improved tests for homogeneity of variances

Communications in Statistics - Simulation and Computation, 2017
ABSTRACTEquality of variances is one of the key assumptions of analysis of variances (ANOVA). There are several testing procedures available to validate this assumption, but it is rare to find a test procedure which controls the type I error rate while providing high statistical power.
Kalanka P. Jayalath, Hon Keung Tony Ng, Ananda B. W. Manage, Kent E. Riggs   +3 more
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Testing for homogeneity: the geometric distribution

Biometrika, 1974
SUMMARY A locally most powerful similar test is constructed for testing the homogeneity of k geometric series against a general class of alternatives. Some properties of the test statistic under the null hypothesis are given, as well as an approximation to its distribution, and an assessment of it.
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A new test for ‘sufficient homogeneity’

The Analyst, 2001
Certified reference materials and materials distributed in proficiency testing need to be 'sufficiently homogeneous', that is, the variance in the mean composition of the distributed portions of the material must be negligibly small in relation to the variance of the analytical result produced when the material is in normal use.
T, Fearn, M, Thompson
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On testing for homogeneity of the covariance matrices

Korean Journal of Computational & Applied Mathematics, 2001
Summary: Testing equality of covariance matrices of \(k\) populations has long been an interesting issue in statistical inference. To overcome the sparseness of data points in a high-dimensional space and deal with the general cases, we suggest several projection pursuit type statistics.
Zhang, Xiaoning, Jing, Ping, Ji, Xiaoming   +2 more
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Tests of homogeneity for spatial populations

Statistics & Probability Letters, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Testing for homogeneity

2000
In this chapter, various tests for homogeneity will be discussed. In section 5.1, an exact test for the case of normal, homoskedastic errors which are independent in time is derived. This test corresponds to Anderson’s U test (see Anderson 1984, 298ff).
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Asymptotic Properties of Homogeneity Tests

Biometrika, 1973
SUMMARY Tests for the homogeneity of samples from the Poisson and Gamma distributions are considered based on the C(ac) procedure of Neyman and on maximum likelihood estimators. These are shown to be equivalent in spite of the fact that the null hypothesis lies on the boundary of the parameter space, which is contrary to the assumptions under which the
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Testing a homogeneity of stochastic processes

Kybernetika, 2007
Summary: This paper concentrates on modeling data that can be described by a homogeneous or non-homogeneous Poisson process. The goal is to decide whether the intensity of the process is constant or not. In technical practice, e.g., it means to decide whether the reliability of the system remains the same or if it is improving or deteriorating.
Jaromír Antoch, Daniela Jarusková
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Remarks on tests of homogeneity

Journal of Statistical Planning and Inference, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Johnson, Norman L., Kotz, Samuel
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A Revisit on Tests for Homogeneity of the Risk Difference

Biometrics, 2000
Summary. Lipsitz et al. (1998, Biometrics54, 148–160) discussed testing the homogeneity of the risk difference for a series of 2 × 2 tables. They proposed and evaluated several weighted test statistics, including the commonly used weighted least squares test statistic. Here we suggest various important improvements on these test statistics.
Lui, Kung-Jong, Kelly, Colleen
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