An accurate method for approximate conditional and Bayesian inference about linear regression models from censored data期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

An accurate method for approximate conditional and Bayesian inference about linear regression models from censored data

Authors:	DICICCIO, THOMAS J. FIELD, CHRISTOPHER A.

Affiliation:	¹Department of Statistics, Stanford University Stanford, California 94305, U. S.A. ²Department of Mathematics, Statistics and Computing Science, Dalhousie University Halifax, Nova Scotia, Canada B3H 3J5

Abstract:

Keywords:	Asymptotic normality Extreme-value distribution Maximum likelihood Nonnormal linear regression Quantile Signed root likelihood ratio statistic Student's t distribution Tail probability approximation
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