Accurate confidence intervals in regression analyses of non-normal data

Autor:	Robert J. Boik
Rok vydání:	2006
Předmět:	Statistics and Probability Percentile education Statistics Linear model Confidence distribution Kurtosis Edgeworth series Robust confidence intervals Confidence interval CDF-based nonparametric confidence interval Mathematics
Zdroj:	Annals of the Institute of Statistical Mathematics. 60:61-83
ISSN:	1572-9052 0020-3157
Popis:	A linear model in which random errors are distributed independently and identically according to an arbitrary continuous distribution is assumed. Second- and third-order accurate confidence intervals for regression parameters are constructed from Charlier differential series expansions of approximately pivotal quantities around Student’s t distribution. Simulation verifies that small sample performance of the intervals surpasses that of conventional asymptotic intervals and equals or surpasses that of bootstrap percentile-t and bootstrap percentile-|t| intervals under mild to marked departure from normality.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8a768c4ef357b1585372de75754bb3a2 https://doi.org/10.1007/s10463-006-0085-1 Zobrazit plný text záznamu Full text from SpringerLink