Testing the equality of the laws of two strictly stationary processes
Sign Up to like & getrecommendations! Published in 2022 at "Statistical Inference for Stochastic Processes"
DOI: 10.1007/s11203-022-09272-w
Abstract: In this paper we propose to generalize the recent works of [4] and [3] on the comparison of the marginal distributions of two strictly stationary processes. Our aim is to test the equality the whole… read more here.
Keywords: testing equality; strictly stationary; processes testing; stationary processes ... See more keywords
Testing the equality of a large number of populations
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DOI: 10.1007/s11749-021-00769-9
Abstract: Given k independent samples with finite but arbitrary dimension, this paper deals with the problem of testing for the equality of their distributions that can be continuous, discrete or mixed. In contrast to the classical… read more here.
Keywords: testing equality; large number; equality; test ... See more keywords
Power comparison of data depth-based nonparametric tests for testing equality of locations
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DOI: 10.1080/00949655.2016.1269329
Abstract: ABSTRACT In the recent years, the notion of data depth has been used in nonparametric multivariate data analysis since it gives natural ‘centre-outward’ ordering of multivariate data points with respect to the given data cloud.… read more here.
Keywords: testing equality; data depth; nonparametric tests; equality locations ... See more keywords
Testing the equality of several multivariate normal mean vectors under heteroscedasticity: A fiducial approach and an approximate test
Sign Up to like & getrecommendations! Published in 2018 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2017.1324984
Abstract: ABSTRACT We consider the problem of testing the equality of several multivariate normal mean vectors under heteroscedasticity. We first construct a fiducial confidence region (FCR) for the differences between normal mean vectors and we then… read more here.
Keywords: mean vectors; testing equality; equality several; test ... See more keywords