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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:

2011年03期

Page:

7-12

Research Field:

数学

Publishing date:

Info

Title:

Parameter Estimations Under Progressive Type-Ⅰ Interval Censoring

Author(s):

Ren Rui; Zhou Xiuqing

School of Mathematical Sciences,Nanjing Normal University,Nanjing 210046,China

Keywords:

progressively type-I interval censoring; EM algorithm; missing information principle; consistency; asymptotic normality

PACS:

O212.1

DOI:

-

Abstract:

EM algorithm are used to obtain the maximum likelihood estimates of parameters when the data are progressively type-I interval censoring． The consistency and asymptotic of the MLE are proved and asymptotic covariances are computed by means of the missing information principle．

References:

［1］ Ng H K T，Chan P S，Balakrishnan N． Estimation of parameters from progressively censored data using EM algorithm ［J］． Computational Statistics and Data Analysis，2002，39: 371-386．
［2］ Lin Chientai，Balakrishnan N． Asymptotic properties of maximum likelihood estimators based on progressive Type-Ⅱ censoring ［J］． Metrika，2010-03-25． Online First．
［3］ Aggarwala R． Progressively interval censoring: Some mathematical results with application to inference［J］． Communications in Statistics-Theory and Methods，2001，30: 1 921-1 935．
［4］ Chen D G，Lio Y L． Parameter estimations for generalized exponential distribution under progressive type-I interval censoring ［J］． Computational Statistics and Data Analysis，2010，54: 1 581-1 591．
［5］ Louis T A． Finding the observed information matrix when using the EM algorithm［J］． R Stat Soc Series B，1982，44: 226- 233．
［6］ Cramér H． Mathematical Methods of Statistics［M］． Princeton: Princeton University Press， 1946．

Memo

Memo:

-

Common functions

Last Update: 2011-09-15