Journal of Statistical Theory and Applications

Volume 15, Issue 1, March 2016, Pages 96 - 107

On the Parametric Maximum Likelihood Estimator for Independent but Non-identically Distributed Observations with Application to Truncated Data

Authors
Fanny Leroy, Jean-Yves Dauxois, Pascale Tubert-Bitter
Corresponding Author
Fanny Leroy
Received 21 January 2014, Accepted 16 June 2015, Available Online 1 March 2016.
DOI
10.2991/jsta.2016.15.1.8How to use a DOI?
Keywords
Parametric maximum likelihood estimator; Independent non-identically distributed observations; Consistency; Asymptotic normality; Truncated data.
Abstract

We investigate the parametric maximum likelihood estimator for truncated data when the truncation value is different according to the observed individual or item. We extend Lehmann’s proof (1983) of the asymptotic properties of the parametric maximum likelihood estimator in the case of independent nonidentically distributed observations. Two cases are considered: either the number of distinct probability distribution functions that can be observed in the population from which the sample comes from is finite or this number is infinite. Sufficient conditions for consistency and asymptotic normality are provided for both cases.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
15 - 1
Pages
96 - 107
Publication Date
2016/03/01
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
10.2991/jsta.2016.15.1.8How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Fanny Leroy
AU  - Jean-Yves Dauxois
AU  - Pascale Tubert-Bitter
PY  - 2016
DA  - 2016/03/01
TI  - On the Parametric Maximum Likelihood Estimator for Independent but Non-identically Distributed Observations with Application to Truncated Data
JO  - Journal of Statistical Theory and Applications
SP  - 96
EP  - 107
VL  - 15
IS  - 1
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2016.15.1.8
DO  - 10.2991/jsta.2016.15.1.8
ID  - Leroy2016
ER  -