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34 changes: 30 additions & 4 deletions docs/LICENSE.html
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39 changes: 33 additions & 6 deletions docs/index.html
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Expand All @@ -1788,12 +1812,13 @@ <h3>${suggestion.title}</h3>
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Expand All @@ -2521,12 +2547,13 @@ <h3>Contents</h3>
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<p>Who: <a href="https://oliviergimenez.github.io/">Olivier Gimenez</a><br />
When:
Nov 21-Nov 28-Dec 5, 2024<br />
<del>March 22-23-25-26, 2021</del><br />
<del>Nov 25-Dec 2-Dec 9, 2021</del><br />
<del>April 11-12, 2022</del><br />
<del>Sept 22-23, 2022</del><br />
<del>Nov 24-Dec 1-Dec 8, 2022</del><br />
Nov 23-Nov 30-Dec 7, 2023</p>
<del>Nov 23-Nov 30-Dec 7, 2023</del></p>
<p>Where:
<del>Zoom</del><br />
<del>Biodiversity Ecology Evolution Master, Montpellier University</del><br />
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6 changes: 3 additions & 3 deletions docs/search.json
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"title": "Bayesian statistics with R",
"author": [],
"contents": "\n\nContents\nSchedule\nLearning objectives\nRequirements\nCredits\nCorrections\nReuse\n\n\nWho: Olivier Gimenez\nWhen:\nMarch 22-23-25-26, 2021Nov 25-Dec 2-Dec 9, 2021April 11-12, 2022Sept 22-23, 2022Nov 24-Dec 1-Dec 8, 2022\nNov 23-Nov 30-Dec 7, 2023\nWhere:\nZoomBiodiversity Ecology Evolution Master, Montpellier UniversityCollège Doctoral, Montpellier UniversityCollège Doctoral, Montpellier University\nBiodiversity Ecology Evolution Master, Montpellier University\n\n\nSchedule\nAn introduction to Bayesian inference [lecture | practical 1 | video]\nThe likelihood [lecture | practical 2 | video]\nBayesian analyses by hand [lecture | video]\nA detour to explore priors [lecture | practical 3 | practical 4| video]\nMarkov chains Monte Carlo methods (MCMC) [lecture | video]\nBayesian analyses in R with the Jags software [lecture | R script | practical 5 | practical 6 | video]\nContrast scientific hypotheses with model selection [lecture | practical 7 | video]\nHeterogeneity and multilevel models (aka mixed models) [lecture | R script | practical 8 | practical 9 | video]\nLearning objectives\nTry and demystify Bayesian statistics, and MCMC methods\nMake the difference between Bayesian and Frequentist analyses\nUnderstand the Methods section of a paper that does Bayesian stuff\nRun Bayesian analyses with R (in Jags)\nRequirements\nYou need to have R and RStudio installed\nDownload Jags from sourceforge and install it\nInstall the following R packages: tidyverse, here, lme4, visreg, lattice, brms and R2jags. You can install them all at once by running the following code in the R command line:\n\n\ninstall.packages(c(\"tidyverse\", \"R2jags\", \"here\", \"lme4\", \"visreg\", \"lattice\", \"brms\"))\n\n\nCredits\nMany slides are from a workshop we used to run a loooong time ago with Ruth King, Byron Morgan and Steve Brooks. I also re-used or adapted slides by Richard McElreath, Kerrie Mengersen, Francisco Rodriguez Sanchez, Jim Albert and Jingchen Hu, Tristan Marh, Jason Matthiopoulos, a paper by Michael McCarthy and Pip Masters, Andrés Lopez-Sepulcre and John Kruschke’ book cover. The sources for the images are James Kulich, Matt Buck, xkcd and Mike West.\nCorrections\nIf you spot a typo or an error, find a bug, want to suggest changes, or have trouble running the code, please file an issue or get back to me\nReuse\nText and figures are licensed under Creative Commons Attribution CC BY 4.0. Any computer code (R, HTML, CSS, etc.) in slides and worksheets, including in slide and worksheet sources, is also licensed under MIT.\n\n\n\n",
"last_modified": "2023-11-30T20:20:36+01:00"
"contents": "\n\nContents\nSchedule\nLearning objectives\nRequirements\nCredits\nCorrections\nReuse\n\n\nWho: Olivier Gimenez\nWhen:\nNov 21-Nov 28-Dec 5, 2024March 22-23-25-26, 2021Nov 25-Dec 2-Dec 9, 2021April 11-12, 2022Sept 22-23, 2022Nov 24-Dec 1-Dec 8, 2022Nov 23-Nov 30-Dec 7, 2023\nWhere:\nZoomBiodiversity Ecology Evolution Master, Montpellier UniversityCollège Doctoral, Montpellier UniversityCollège Doctoral, Montpellier University\nBiodiversity Ecology Evolution Master, Montpellier University\n\n\nSchedule\nAn introduction to Bayesian inference [lecture | practical 1 | video]\nThe likelihood [lecture | practical 2 | video]\nBayesian analyses by hand [lecture | video]\nA detour to explore priors [lecture | practical 3 | practical 4| video]\nMarkov chains Monte Carlo methods (MCMC) [lecture | video]\nBayesian analyses in R with the Jags software [lecture | R script | practical 5 | practical 6 | video]\nContrast scientific hypotheses with model selection [lecture | practical 7 | video]\nHeterogeneity and multilevel models (aka mixed models) [lecture | R script | practical 8 | practical 9 | video]\nLearning objectives\nTry and demystify Bayesian statistics, and MCMC methods\nMake the difference between Bayesian and Frequentist analyses\nUnderstand the Methods section of a paper that does Bayesian stuff\nRun Bayesian analyses with R (in Jags)\nRequirements\nYou need to have R and RStudio installed\nDownload Jags from sourceforge and install it\nInstall the following R packages: tidyverse, here, lme4, visreg, lattice, brms and R2jags. You can install them all at once by running the following code in the R command line:\n\n\ninstall.packages(c(\"tidyverse\", \"R2jags\", \"here\", \"lme4\", \"visreg\", \"lattice\", \"brms\"))\n\n\nCredits\nMany slides are from a workshop we used to run a loooong time ago with Ruth King, Byron Morgan and Steve Brooks. I also re-used or adapted slides by Richard McElreath, Kerrie Mengersen, Francisco Rodriguez Sanchez, Jim Albert and Jingchen Hu, Tristan Marh, Jason Matthiopoulos, a paper by Michael McCarthy and Pip Masters, Andrés Lopez-Sepulcre and John Kruschke’ book cover. The sources for the images are James Kulich, Matt Buck, xkcd and Mike West.\nCorrections\nIf you spot a typo or an error, find a bug, want to suggest changes, or have trouble running the code, please file an issue or get back to me\nReuse\nText and figures are licensed under Creative Commons Attribution CC BY 4.0. Any computer code (R, HTML, CSS, etc.) in slides and worksheets, including in slide and worksheet sources, is also licensed under MIT.\n\n\n\n",
"last_modified": "2024-10-17T20:28:07+02:00"
},
{
"path": "LICENSE.html",
"author": [],
"contents": "\n\nContents\nMIT License\n\nMIT License\nCopyright (c) 2021 Olivier Gimenez\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the “Software”), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\nTHE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n\n",
"last_modified": "2023-11-30T20:20:36+01:00"
"last_modified": "2024-10-17T20:28:07+02:00"
}
],
"collections": []
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3 changes: 2 additions & 1 deletion index.Rmd
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Who: [Olivier Gimenez](https://oliviergimenez.github.io/)
When:
Nov 21-Nov 28-Dec 5, 2024
~~March 22-23-25-26, 2021~~
~~Nov 25-Dec 2-Dec 9, 2021~~
~~April 11-12, 2022~~
~~Sept 22-23, 2022~~
~~Nov 24-Dec 1-Dec 8, 2022~~
Nov 23-Nov 30-Dec 7, 2023
~~Nov 23-Nov 30-Dec 7, 2023~~

Where:
~~Zoom~~
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2 changes: 1 addition & 1 deletion slides/motivations.Rmd
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Expand Up @@ -3,7 +3,7 @@ title: |
| Bayesian statistics with R
| 1. An introduction to Bayesian inference
author: "Olivier Gimenez"
date: "November-December 2023"
date: "November-December 2024"
output:
beamer_presentation:
fig_caption: no
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Binary file modified slides/motivations.pdf
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