Tests for validity of the semiparametric heteroskedastic transformation model

Kód výsledku v IS VaVaI

RIV/00216208:11320/20:10418155 - isvavai.cz

Výsledek na webu

https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=XPbubQEMSW

DOI - Digital Object Identifier

10.1016/j.csda.2019.106895

Jazyk výsledku

angličtina

Název v původním jazyce

Tests for validity of the semiparametric heteroskedastic transformation model

Popis výsledku v původním jazyce

There exist a number of tests for assessing the nonparametric heteroskedastic location scale assumption. The goodness-of-fit tests considered are for the more general hypothesis of the validity of this model under a parametric functional transformation on the response variable, specifically testing for independence between the regressors and the errors in a model where the transformed response is just a location/scale shift of the error is considered. The proposed criteria use the familiar factorization property of the joint characteristic function under independence. The difficulty is that the errors are unobserved and hence one needs to employ properly estimated residuals in their place. The limit distribution of the test statistics is studied under the null hypothesis as well as under alternatives. and also a resampling procedure is suggested in order to approximate the critical values of the tests. This resampling is subsequently employed in a series of Monte Carlo experiments that illustrate the finite-sample properties of the new test. The performance of related test statistics for normality and symmetry of errors is also investigated, and application of our methods on real data sets is provided. (C) 2019 Elsevier B.V. All rights reserved.

Název v anglickém jazyce

Tests for validity of the semiparametric heteroskedastic transformation model

Popis výsledku anglicky

There exist a number of tests for assessing the nonparametric heteroskedastic location scale assumption. The goodness-of-fit tests considered are for the more general hypothesis of the validity of this model under a parametric functional transformation on the response variable, specifically testing for independence between the regressors and the errors in a model where the transformed response is just a location/scale shift of the error is considered. The proposed criteria use the familiar factorization property of the joint characteristic function under independence. The difficulty is that the errors are unobserved and hence one needs to employ properly estimated residuals in their place. The limit distribution of the test statistics is studied under the null hypothesis as well as under alternatives. and also a resampling procedure is suggested in order to approximate the critical values of the tests. This resampling is subsequently employed in a series of Monte Carlo experiments that illustrate the finite-sample properties of the new test. The performance of related test statistics for normality and symmetry of errors is also investigated, and application of our methods on real data sets is provided. (C) 2019 Elsevier B.V. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computational Statistics and Data Analysis

ISSN

0167-9473

e-ISSN

—

Svazek periodika

144

Číslo periodika v rámci svazku

Neuveden

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

17

Strana od-do

—

Kód UT WoS článku

000515446200037

EID výsledku v databázi Scopus

2-s2.0-85077238030