Authors: Chown, Justin
Bissantz, Nicolai
Dette, Holger
Title: Goodness-of-fit testing the error distribution in multivariate indirect regression
Language (ISO): en
Abstract: We propose a goodness-of-fit test for the distribution of errors from a multivariate indirect regression model. 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.
Subject Headings: hypothesis testing
multivariate regression
inverse problems
indirect regression estimator
Issue Date: 2018
Appears in Collections:Sonderforschungsbereich (SFB) 823

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