Consistency of Parametric MLE Under Mixed Case Interval Censoring

Standard

Consistency of Parametric MLE Under Mixed Case Interval Censoring. / Korobeynikov, Anton.

In: Communications in Statistics Part B: Simulation and Computation, Vol. 41, No. 7, 2012, p. 1083-1092.

Research output: Contribution to journal › Article

Author

Korobeynikov, Anton. / Consistency of Parametric MLE Under Mixed Case Interval Censoring. In: Communications in Statistics Part B: Simulation and Computation. 2012 ; Vol. 41, No. 7. pp. 1083-1092.

BibTeX

@article{a449b4d175d04842ac39f4c710ed02f0,

title = "Consistency of Parametric MLE Under Mixed Case Interval Censoring",

abstract = "We study estimation in parametric models. It is assumed that the variable of interest cannot be observed directly so a mixed case interval censoring model is used instead. The data consist of a sequence of times of inspection events and a mark variable. The mark variable indicates the endpoints of the inspection interval where the variable of interest is located. The main result is an extension of Wald's theorem for complete data to the censored case. The theorem provides sufficient conditions for consistency of the maximum likelihood estimates. The conditions obtained are much weaker compared to the standard Cram{\'e}r-like regularity conditions.",

author = "Anton Korobeynikov",

year = "2012",

doi = "10.1080/03610918.2012.625811",

language = "English",

volume = "41",

pages = "1083--1092",

journal = "Communications in Statistics Part B: Simulation and Computation",

issn = "0361-0918",

publisher = "Taylor & Francis",

number = "7",

}

RIS

TY - JOUR

T1 - Consistency of Parametric MLE Under Mixed Case Interval Censoring

AU - Korobeynikov, Anton

PY - 2012

Y1 - 2012

N2 - We study estimation in parametric models. It is assumed that the variable of interest cannot be observed directly so a mixed case interval censoring model is used instead. The data consist of a sequence of times of inspection events and a mark variable. The mark variable indicates the endpoints of the inspection interval where the variable of interest is located. The main result is an extension of Wald's theorem for complete data to the censored case. The theorem provides sufficient conditions for consistency of the maximum likelihood estimates. The conditions obtained are much weaker compared to the standard Cramér-like regularity conditions.

AB - We study estimation in parametric models. It is assumed that the variable of interest cannot be observed directly so a mixed case interval censoring model is used instead. The data consist of a sequence of times of inspection events and a mark variable. The mark variable indicates the endpoints of the inspection interval where the variable of interest is located. The main result is an extension of Wald's theorem for complete data to the censored case. The theorem provides sufficient conditions for consistency of the maximum likelihood estimates. The conditions obtained are much weaker compared to the standard Cramér-like regularity conditions.

U2 - 10.1080/03610918.2012.625811

DO - 10.1080/03610918.2012.625811

M3 - Article

VL - 41

SP - 1083

EP - 1092

JO - Communications in Statistics Part B: Simulation and Computation

JF - Communications in Statistics Part B: Simulation and Computation

SN - 0361-0918

IS - 7

ER -

ID: 5322073