Rank tests in regression model based on minimum distance estimates

Title:

Rank tests in regression model based on minimum distance estimates

Creator:

Navrátil, Radim

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:4bb9ac0e-aade-4ae4-96c4-88c4d8f4cb25
uuid:4bb9ac0e-aade-4ae4-96c4-88c4d8f4cb25

Subject:

measurement errors, minimum distance estimates, and rank tests

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

In this paper a new rank test in a linear regression model is introduced. The test statistic is based on a certain minimum distance estimator, however, unlike classical rank tests in regression it is not a simple linear rank statistic. Its exact distribution under the null hypothesis is derived, and further, the asymptotic distribution both under the null hypothesis and the local alternative is investigated. It is shown that the proposed test is applicable in measurement error models. Finally, a simulation study is conducted to show a good performance of the test. It has, in some situations, a greater power than the widely used Wilcoxon rank test.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[909]-922

Source:

Kybernetika | 2015 Volume:51 | Number:6

Harvested from:

CDK

Metadata only:

false