Stochastic monotonicity of the MLEs of parameters in exponential simple step-stress models under Type-I and Type-II censoring

被引:12
|
作者
Balakrishnan, N. [2 ]
Iliopoulos, G. [1 ]
机构
[1] Univ Piraeus, Dept Stat & Insurance Sci, Piraeus 18534, Greece
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada
关键词
EXACT INFERENCE;
D O I
10.1007/s00184-009-0243-6
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In two recent papers by Balakrishnan et al. (J Qual Technol 39:35-47, 2007; Ann Inst Stat Math 61:251-274, 2009), the maximum likelihood estimators theta(1) and theta(2) of the parameters theta(1) and theta(2) have been derived in the framework of exponential simple step-stress models under Type-II and Type-I censoring, respectively. Here, we prove that these estimators are stochastically monotone with respect to theta(1) and theta(2), respectively, which has been conjectured in these papers and then utilized to develop exact conditional inference for the parameters theta(1) and theta(2). For proving these results, we have established a multivariate stochastic ordering of a particular family of trinomial distributions under truncation, which is also of independent interest.
引用
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页码:89 / 109
页数:21
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