Rejection rates of bootstrapped and exact heteroskedasticity tests in response to skedastic function and normal or skewed disturbances

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F23%3A43919827" target="_blank" >RIV/62156489:43110/23:43919827 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1080/03610918.2021.1915335" target="_blank" >https://doi.org/10.1080/03610918.2021.1915335</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/03610918.2021.1915335" target="_blank" >10.1080/03610918.2021.1915335</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Rejection rates of bootstrapped and exact heteroskedasticity tests in response to skedastic function and normal or skewed disturbances

Popis výsledku v původním jazyce

This study focuses on examining the power of bootstrapped and exact tests to detect variance heterogeneity in linear models via Monte Carlo. Three independent MC schemes were set up corresponding to distinct forms of heteroskedasticity, degree of heteroskedasticity and with or without normality. The tests produced unequal power in the simulated combinations; some performed poorly, when exposed to the unusual type of heteroskedasticity from the point of the test. The Bamset LR test had adequate power for most skedastic functions and should be extensively used. Park&apos;s test had inadequate power in most scenarios. The power of White&apos;s test varied strongly depending on the skedastic function. The bootstrapped tests had generally lower power and were often oversized, although the only resampled Harrison and McCabe test had outstanding power in several MC schemes. Reduced power and increased Type I Error Rates were noticed in most exact or resampled tests with skewed disturbances.

Název v anglickém jazyce

Rejection rates of bootstrapped and exact heteroskedasticity tests in response to skedastic function and normal or skewed disturbances

Popis výsledku anglicky

This study focuses on examining the power of bootstrapped and exact tests to detect variance heterogeneity in linear models via Monte Carlo. Three independent MC schemes were set up corresponding to distinct forms of heteroskedasticity, degree of heteroskedasticity and with or without normality. The tests produced unequal power in the simulated combinations; some performed poorly, when exposed to the unusual type of heteroskedasticity from the point of the test. The Bamset LR test had adequate power for most skedastic functions and should be extensively used. Park&apos;s test had inadequate power in most scenarios. The power of White&apos;s test varied strongly depending on the skedastic function. The bootstrapped tests had generally lower power and were often oversized, although the only resampled Harrison and McCabe test had outstanding power in several MC schemes. Reduced power and increased Type I Error Rates were noticed in most exact or resampled tests with skewed disturbances.

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

2023

Kód důvěrnosti údajů

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

Název periodika

Communications in Statistics. Simulation and Computation

ISSN

0361-0918

e-ISSN

1532-4141

Svazek periodika

52

Číslo periodika v rámci svazku

6

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

16

Strana od-do

2765-2780

Kód UT WoS článku

000648049500001

EID výsledku v databázi Scopus

2-s2.0-85105457947