Consistency of maximum likelihood estimators in general random effects models for binary data
- Author
- BUTLER, S. M; LOUIS, T. A
University of Kentucky, United States
University of Minnesota, United States - Source
Annals of statistics. 1997, Vol 25, Num 1, pp 351-377 ; ref : 28 ref
- CODEN
- ASTSC7
- ISSN
- 0090-5364
- Scientific domain
- Mathematics
- Publisher
- Institute of Mathematical Statistics, Hayward, CA
- Publication country
- United States
- Document type
- Article
- Language
- English
- Keyword (fr)
- Donnée binaire Modèle linéaire Régression logistique Convergence martingale Estimateur maximum vraisemblance Loi mélange Modèle effet aléatoire Mélange non paramétrique
- Keyword (en)
- Binary data Linear model Logistic regression Maximum likelihood estimator Mixing distribution Random effect model Nonparametric mixing
- Keyword (es)
- Dato binario Modelo lineal Regresión logística
- Classification
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02D Decision theory
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02E Sampling theory, sample surveys
- Pascal
- 001 Exact sciences and technology / 001A Sciences and techniques of general use / 001A02 Mathematics / 001A02H Probability and statistics / 001A02H02 Statistics / 001A02H02K Experimental design
- Discipline
- Mathematics
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 2686603
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.1214/aos/1034276633 
https://dx.doi.org/10.1214/aos/1034276633
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