Publications

Goodness-of-fit testing the error distribution in multivariate indirect regression

Chown, J. and Bissantz, N. and Dette, H.

ELECTRONIC JOURNAL OF STATISTICS
Volume: 13 Pages: 2658-2685
DOI: 10.1214/19-EJS1591
Published: 2019

Abstract
We propose a goodness-of-fit test for the distribution of errors from a multivariate indirect regression model, which we assume belongs to a location-scale family under the null hypothesis. The test statistic is based on the Khmaladze transformation of the empirical process of standardized residuals. This goodness-of-fit test is consistent at the root-n rate of convergence, and the test can maintain power against local alternatives converging to the null at a root-n rate. © 2019, Institute of Mathematical Statistics. All rights reserved.

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