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Integral transform methods in goodness-of-fit testing, II: the Wishart distributions
Annals of the Institute of Statistical Mathematics, 2019We initiate the study of goodness-of-fit testing for data consisting of positive definite matrices. Motivated by the appearance of positive definite matrices in numerous applications, including factor analysis, diffusion tensor imaging, volatility models
Elena Hadjicosta, D. Richards
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Goodness-of-Fit Testing for the Degradation Models in Reliability Analysis
IEEE International Conference on Actual Problems of Electronics Instrument Engineering, 2018In this paper, the gamma and Wiener degradation models with covariates are considered. It is assumed that the independent increments of the degradation index have gamma distribution for the gamma degradation model and normal distribution in case of the ...
E. Chimitova, E. S. Chetvertakova
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2018
Based on the substitution principle, we derive one-sample goodness-of-fit tests of Kolmogorov-Smirnov and Cramer-von Mises type, respectively. In the case of a completely specified null hypothesis, these tests are distribution-free, if the cumulative distribution function under the null is a continuous function. In the case of composite null hypotheses,
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Based on the substitution principle, we derive one-sample goodness-of-fit tests of Kolmogorov-Smirnov and Cramer-von Mises type, respectively. In the case of a completely specified null hypothesis, these tests are distribution-free, if the cumulative distribution function under the null is a continuous function. In the case of composite null hypotheses,
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1998
Goodness-of-fit tests are used to validate the use of a particular distribution to describe data arising from sampling or experimentation. Numerous goodness-of-fit tests have been developed. The power divergence family of test statistics includes Pearson’s chi-squared test, the likelihood ratio test, and the Freeman-Tukey chi-squared test.
Linda J. Young, Jerry H. Young
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Goodness-of-fit tests are used to validate the use of a particular distribution to describe data arising from sampling or experimentation. Numerous goodness-of-fit tests have been developed. The power divergence family of test statistics includes Pearson’s chi-squared test, the likelihood ratio test, and the Freeman-Tukey chi-squared test.
Linda J. Young, Jerry H. Young
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2001
Goodness-of-fit techniques are essential for determining whether hypothetical models fit observed data. When at all reasonable, exact tests are preferred to either nonasymptotic or, especially, asymptotic tests. In addition, the structures of these tests yield entirely different detection capabilities for varying alternatives. A selection of techniques
Paul W. Mielke, Kenneth J. Berry
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Goodness-of-fit techniques are essential for determining whether hypothetical models fit observed data. When at all reasonable, exact tests are preferred to either nonasymptotic or, especially, asymptotic tests. In addition, the structures of these tests yield entirely different detection capabilities for varying alternatives. A selection of techniques
Paul W. Mielke, Kenneth J. Berry
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2011
Goodness-of-fit tests are batteries of tests that test that the distribution of a sample is equal to some fixed-in-advance distribution. We already saw Q–Q plots in Chap. 5 where the samples were compared to some theoretical distributions but in a descriptive fashion, without formal inference.
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Goodness-of-fit tests are batteries of tests that test that the distribution of a sample is equal to some fixed-in-advance distribution. We already saw Q–Q plots in Chap. 5 where the samples were compared to some theoretical distributions but in a descriptive fashion, without formal inference.
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Length tests for goodnesss-of-fit
Biometrika, 1991Consider an i.i.d. sample X 1,..., X n with distribution function F, which throughout is assumed to be twice continuously differentiable with support [0,1] and strictly positive derivative on [0,1]. Denote by $$0={X_{0:n}}\leqslant {X_{1:n}}\leqslant\cdots\leqslant{X_{n:n}}\leqslant{X_{n+1:n}}=1$$ (1) the order statistics, and the spacings by
Reschenhofer, Erhard, Bomze, Immanuel
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»Smooth test» for goodness of fit
Scandinavian Actuarial Journal, 1937Abstract Dedicated to the memory of Karl Pearson (27 March 1857—27 April 1936) who originated the problem of a test for goodness of fit and was first to advance its solution.
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