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Methods of statistical model estimation
Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for st...
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| Lenguaje: | eng |
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CRC Press
2013
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| Acceso en línea: | http://cds.cern.ch/record/1604095 |
| _version_ | 1780931584736624640 |
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| author | Hilbe, Joseph |
| author_facet | Hilbe, Joseph |
| author_sort | Hilbe, Joseph |
| collection | CERN |
| description | Methods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting. The text presents algorithms for the estimation of a variety of regression procedures using maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R code is constructed for each method. Th |
| id | cern-1604095 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2013 |
| publisher | CRC Press |
| record_format | invenio |
| spelling | cern-16040952021-04-21T22:24:57Zhttp://cds.cern.ch/record/1604095engHilbe, JosephMethods of statistical model estimationMathematical Physics and MathematicsMethods of Statistical Model Estimation examines the most important and popular methods used to estimate parameters for statistical models and provide informative model summary statistics. Designed for R users, the book is also ideal for anyone wanting to better understand the algorithms used for statistical model fitting. The text presents algorithms for the estimation of a variety of regression procedures using maximum likelihood estimation, iteratively reweighted least squares regression, the EM algorithm, and MCMC sampling. Fully developed, working R code is constructed for each method. ThCRC Pressoai:cds.cern.ch:16040952013 |
| spellingShingle | Mathematical Physics and Mathematics Hilbe, Joseph Methods of statistical model estimation |
| title | Methods of statistical model estimation |
| title_full | Methods of statistical model estimation |
| title_fullStr | Methods of statistical model estimation |
| title_full_unstemmed | Methods of statistical model estimation |
| title_short | Methods of statistical model estimation |
| title_sort | methods of statistical model estimation |
| topic | Mathematical Physics and Mathematics |
| url | http://cds.cern.ch/record/1604095 |
| work_keys_str_mv | AT hilbejoseph methodsofstatisticalmodelestimation |