Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB

This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodolog...

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Detalles Bibliográficos
Autor principal: Millar, Russell B
Lenguaje:eng
Publicado: John Wiley & Sons 2011
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/1437298
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author Millar, Russell B
author_facet Millar, Russell B
author_sort Millar, Russell B
collection CERN
description This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statis
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institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2011
publisher John Wiley & Sons
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spelling cern-14372982021-04-22T00:34:25Zhttp://cds.cern.ch/record/1437298engMillar, Russell BMaximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMBMathematical Physics and MathematicsThis book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statisJohn Wiley & Sonsoai:cds.cern.ch:14372982011
spellingShingle Mathematical Physics and Mathematics
Millar, Russell B
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title_full Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title_fullStr Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title_full_unstemmed Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title_short Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB
title_sort maximum likelihood estimation and inference: with examples in r, sas and admb
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1437298
work_keys_str_mv AT millarrussellb maximumlikelihoodestimationandinferencewithexamplesinrsasandadmb

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