Rethinking: an R package for fitting and manipulating bayesian models version 1.56
The rethinking R package began as an instructional aid for a PhD course on applied Bayesian statistics. It has since grown into much more. Its motivation is to provide (1) a very flexible modeling syntax that closely resembles typical mathematical notation and (2) access to both maximum a posteriori...
Gespeichert in:
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
2020
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| Ausgabe: | 2.00 |
| Schlagworte: | |
| Online-Zugang: | Volltext Zusätzliche Angaben |
| Zusammenfassung: | The rethinking R package began as an instructional aid for a PhD course on applied Bayesian statistics. It has since grown into much more. Its motivation is to provide (1) a very flexible modeling syntax that closely resembles typical mathematical notation and (2) access to both maximum a posteriori (MAP) and Hamiltonian Monte Carlo (HMC, provided by rstan) for model fitting. As a result, rethinking can specify many more types of models than a package like MCMCglmm can, while also using much better sampling algorithms, as provided by rstan. |
| Beschreibung: | 1 Online-Ressource (26 Seiten) |
Internformat
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| 100 | 1 | |a McElreath, Richard |d 1973- |e Verfasser |0 (DE-588)131816780 |4 aut | |
| 245 | 1 | 0 | |a Rethinking |b an R package for fitting and manipulating bayesian models version 1.56 |c Richard McElreath |
| 250 | |a 2.00 | ||
| 264 | 1 | |c 2020 | |
| 300 | |a 1 Online-Ressource (26 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
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| 338 | |b cr |2 rdacarrier | ||
| 505 | 8 | |a 1. Overview 1 1.1. Installation 2 1.2. map:Maximumaposteriorifitting 3 1.3. map2stan:HamiltonianMonteCarlo 6 1.4. Posterior predictions with link and sim 11 1.5. WAIC/DIC model comparison and averaging with compare and ensemble 16 1.6. Missing data imputation with map2stan 20 1.7. glimmer: From glmer to map2stan 21 2. Model specification examples 21 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 2.9. 2.10. 2.11. 2.12. 2.13. Linear models 21 Multilevel (mixed effects) models 22 Logistic and binomial models 24 Poisson models 24 Beta-binomial and gamma-Poisson models 25 Gamma and exponential models 25 Zero-inflated Poisson and binomial models 26 Zero-augmented gamma models 26 Multinomial logit models Ordered logit models Gaussian processes Item response theory Factor analysis 26 26 26 26 26 | |
| 520 | 3 | |a The rethinking R package began as an instructional aid for a PhD course on applied Bayesian statistics. It has since grown into much more. Its motivation is to provide (1) a very flexible modeling syntax that closely resembles typical mathematical notation and (2) access to both maximum a posteriori (MAP) and Hamiltonian Monte Carlo (HMC, provided by rstan) for model fitting. As a result, rethinking can specify many more types of models than a package like MCMCglmm can, while also using much better sampling algorithms, as provided by rstan. | |
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| 653 | |a User manual | ||
| 653 | |a Bayesian statistics | ||
| 653 | |a Bayesian statistics course | ||
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| 856 | 4 | 0 | |u http://xcelab.net/R/rethinking_package.pdf |z kostenfrei |3 Volltext |
| 856 | 4 | |u https://github.com/rmcelreath/rethinking |z kostenfrei |3 Zusätzliche Angaben | |
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Datensatz im Suchindex
| _version_ | 1813706132590428160 |
|---|---|
| adam_text | |
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| any_adam_object | |
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| author | McElreath, Richard 1973- |
| author_GND | (DE-588)131816780 |
| author_facet | McElreath, Richard 1973- |
| author_role | aut |
| author_sort | McElreath, Richard 1973- |
| author_variant | r m rm |
| building | Verbundindex |
| bvnumber | BV048599505 |
| callnumber-first | Q - Science |
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| callnumber-search | QA279.5.M3975 |
| callnumber-sort | QA 3279.5 M3975 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | CM 4000 SK 110 MR 2200 SK 830 ES 250 |
| classification_tum | MAT 600f DAT 307f |
| contents | 1. Overview 1 1.1. Installation 2 1.2. map:Maximumaposteriorifitting 3 1.3. map2stan:HamiltonianMonteCarlo 6 1.4. Posterior predictions with link and sim 11 1.5. WAIC/DIC model comparison and averaging with compare and ensemble 16 1.6. Missing data imputation with map2stan 20 1.7. glimmer: From glmer to map2stan 21 2. Model specification examples 21 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 2.9. 2.10. 2.11. 2.12. 2.13. Linear models 21 Multilevel (mixed effects) models 22 Logistic and binomial models 24 Poisson models 24 Beta-binomial and gamma-Poisson models 25 Gamma and exponential models 25 Zero-inflated Poisson and binomial models 26 Zero-augmented gamma models 26 Multinomial logit models Ordered logit models Gaussian processes Item response theory Factor analysis 26 26 26 26 26 |
| ctrlnum | (OCoLC)1354309835 (DE-599)BVBBV048599505 |
| dewey-full | 519.5/42 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/42 |
| dewey-search | 519.5/42 |
| dewey-sort | 3519.5 242 |
| dewey-tens | 510 - Mathematics |
| discipline | Sprachwissenschaft Informatik Soziologie Psychologie Mathematik Literaturwissenschaft |
| discipline_str_mv | Sprachwissenschaft Informatik Soziologie Psychologie Mathematik Literaturwissenschaft |
| edition | 2.00 |
| format | Electronic eBook |
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| language | English |
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| spelling | McElreath, Richard 1973- Verfasser (DE-588)131816780 aut Rethinking an R package for fitting and manipulating bayesian models version 1.56 Richard McElreath 2.00 2020 1 Online-Ressource (26 Seiten) txt rdacontent c rdamedia cr rdacarrier 1. Overview 1 1.1. Installation 2 1.2. map:Maximumaposteriorifitting 3 1.3. map2stan:HamiltonianMonteCarlo 6 1.4. Posterior predictions with link and sim 11 1.5. WAIC/DIC model comparison and averaging with compare and ensemble 16 1.6. Missing data imputation with map2stan 20 1.7. glimmer: From glmer to map2stan 21 2. Model specification examples 21 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 2.9. 2.10. 2.11. 2.12. 2.13. Linear models 21 Multilevel (mixed effects) models 22 Logistic and binomial models 24 Poisson models 24 Beta-binomial and gamma-Poisson models 25 Gamma and exponential models 25 Zero-inflated Poisson and binomial models 26 Zero-augmented gamma models 26 Multinomial logit models Ordered logit models Gaussian processes Item response theory Factor analysis 26 26 26 26 26 The rethinking R package began as an instructional aid for a PhD course on applied Bayesian statistics. It has since grown into much more. Its motivation is to provide (1) a very flexible modeling syntax that closely resembles typical mathematical notation and (2) access to both maximum a posteriori (MAP) and Hamiltonian Monte Carlo (HMC, provided by rstan) for model fitting. As a result, rethinking can specify many more types of models than a package like MCMCglmm can, while also using much better sampling algorithms, as provided by rstan. R Programm (DE-588)4705956-4 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf User manual Bayesian statistics Bayesian statistics course R Programm (DE-588)4705956-4 s Statistisches Modell (DE-588)4121722-6 s DE-604 http://xcelab.net/R/rethinking_package.pdf kostenfrei Volltext https://github.com/rmcelreath/rethinking kostenfrei Zusätzliche Angaben |
| spellingShingle | McElreath, Richard 1973- Rethinking an R package for fitting and manipulating bayesian models version 1.56 1. Overview 1 1.1. Installation 2 1.2. map:Maximumaposteriorifitting 3 1.3. map2stan:HamiltonianMonteCarlo 6 1.4. Posterior predictions with link and sim 11 1.5. WAIC/DIC model comparison and averaging with compare and ensemble 16 1.6. Missing data imputation with map2stan 20 1.7. glimmer: From glmer to map2stan 21 2. Model specification examples 21 2.1. 2.2. 2.3. 2.4. 2.5. 2.6. 2.7. 2.8. 2.9. 2.10. 2.11. 2.12. 2.13. Linear models 21 Multilevel (mixed effects) models 22 Logistic and binomial models 24 Poisson models 24 Beta-binomial and gamma-Poisson models 25 Gamma and exponential models 25 Zero-inflated Poisson and binomial models 26 Zero-augmented gamma models 26 Multinomial logit models Ordered logit models Gaussian processes Item response theory Factor analysis 26 26 26 26 26 R Programm (DE-588)4705956-4 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| subject_GND | (DE-588)4705956-4 (DE-588)4121722-6 |
| title | Rethinking an R package for fitting and manipulating bayesian models version 1.56 |
| title_auth | Rethinking an R package for fitting and manipulating bayesian models version 1.56 |
| title_exact_search | Rethinking an R package for fitting and manipulating bayesian models version 1.56 |
| title_exact_search_txtP | Rethinking an R package for fitting and manipulating bayesian models version 1.56 |
| title_full | Rethinking an R package for fitting and manipulating bayesian models version 1.56 Richard McElreath |
| title_fullStr | Rethinking an R package for fitting and manipulating bayesian models version 1.56 Richard McElreath |
| title_full_unstemmed | Rethinking an R package for fitting and manipulating bayesian models version 1.56 Richard McElreath |
| title_short | Rethinking |
| title_sort | rethinking an r package for fitting and manipulating bayesian models version 1 56 |
| title_sub | an R package for fitting and manipulating bayesian models version 1.56 |
| topic | R Programm (DE-588)4705956-4 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | R Programm Statistisches Modell |
| url | http://xcelab.net/R/rethinking_package.pdf https://github.com/rmcelreath/rethinking |
| work_keys_str_mv | AT mcelreathrichard rethinkinganrpackageforfittingandmanipulatingbayesianmodelsversion156 |