The effects of different choices of order for autoregressive approximation on the Gaussian likelihood estimates for ARMA models

Autor:	M. O. Salau
Rok vydání:	2003
Předmět:	Statistics and Probability Gaussian Monte Carlo method SETAR symbols.namesake Autoregressive model Sample size determination Statistics symbols Autoregressive–moving-average model Autoregressive integrated moving average Statistics Probability and Uncertainty STAR model Mathematics
Zdroj:	Statistical Papers. 44:89-105
ISSN:	1613-9798 0932-5026
DOI:	10.1007/s00362-002-0135-6
Popis:	This paper investigates, by means of Monte Carlo simulation, the effects of different choices of order for autoregressive approximation on the fully efficient parameter estimates for autoregressive moving average models. Four order selection criteria, AIC, BIC, HQ and PKK, were compared and different model structures with varying sample sizes were used to contrast the performance of the criteria. Some asymptotic results which provide a useful guide for assessing the performance of these criteria are presented. The results of this comparison show that there are marked differences in the accuracy implied using these alternative criteria in small sample situations and that it is preferable to apply BIC criterion, which leads to greater precision of Gaussian likelihood estimates, in such cases. Implications of the findings of this study for the estimation of time series models are highlighted.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::46a4f919610b79eb8fd4f00ab4a7f40d https://doi.org/10.1007/s00362-002-0135-6 Zobrazit plný text záznamu Plný text ve formátu PDF