Density testing in a contaminated sample
We study non-parametric tests for checking parametric hypotheses about a multivariate density f of independent identically distributed random vectors Z1,Z2,... which are observed under additional noise with density [psi]. The tests we propose are an extension of the test due to Bickel and Rosenblatt [On some global measures of the deviations of density function estimates, Ann. Statist. 1 (1973) 1071-1095] and are based on a comparison of a nonparametric deconvolution estimator and the smoothed version of a parametric fit of the density f of the variables of interest Zi. In an example the loss of efficiency is highlighted when the test is based on the convolved (but observable) density g=f*[psi] instead on the initial density of interest f.
Year of publication: |
2007
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Authors: | Holzmann, Hajo ; Bissantz, Nicolai ; Munk, Axel |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 98.2007, 1, p. 57-75
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Publisher: |
Elsevier |
Keywords: | Asymptotic normality Deconvolution Goodness of fit Integrated square error Multivariate nonparametric density estimation |
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