Exploration into power of homogeneity and serial correlation tests

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43110%2F13%3A00201067" target="_blank" >RIV/62156489:43110/13:00201067 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.11118/actaun201361041129" target="_blank" >http://dx.doi.org/10.11118/actaun201361041129</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/actaun201361041129" target="_blank" >10.11118/actaun201361041129</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Exploration into power of homogeneity and serial correlation tests

Popis výsledku v původním jazyce

Verification of regression models is primarily based on analysis of error terms and constitutes one of the most important steps in applied regression analysis. In cross-sectional models, the error terms are typically heteroskedastic, while in time seriesregressions the errors are often affected by serial correlation. Consequently, in this paper, we focus on Monte Carlo simulations applied to explore the power of several tests of homogeneity and tests for presence of autocorrelation. In the past decades, the computational power has increased significantly to allow the benefit of simulation from exact distributions, which are not defined explicitly. We will discuss 1) testing of homogeneity for a given number of components in the exponential mixture approximated by subpopulations and 2) simulation of power in several commonly used tests of autocorrelation. For the first case, we consider exact likelihood ratio test (ELR) and exact likelihood ratio test against the alternative with two-c

Název v anglickém jazyce

Exploration into power of homogeneity and serial correlation tests

Popis výsledku anglicky

Verification of regression models is primarily based on analysis of error terms and constitutes one of the most important steps in applied regression analysis. In cross-sectional models, the error terms are typically heteroskedastic, while in time seriesregressions the errors are often affected by serial correlation. Consequently, in this paper, we focus on Monte Carlo simulations applied to explore the power of several tests of homogeneity and tests for presence of autocorrelation. In the past decades, the computational power has increased significantly to allow the benefit of simulation from exact distributions, which are not defined explicitly. We will discuss 1) testing of homogeneity for a given number of components in the exponential mixture approximated by subpopulations and 2) simulation of power in several commonly used tests of autocorrelation. For the first case, we consider exact likelihood ratio test (ELR) and exact likelihood ratio test against the alternative with two-c

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

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Svazek periodika

61

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

1129-1136

Kód UT WoS článku

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EID výsledku v databázi Scopus

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