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  1. mages revised this gist Jul 18, 2018. 1 changed file with 4 additions and 4 deletions.
    8 changes: 4 additions & 4 deletions StanWorkshop2018.md
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    ### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    - [Intro to Stan, including](https://rawgithub.com/InsuranceDataScience/StanWorkshop2018/master/ericnovik/stan_man_1.html):
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    @@ -15,7 +15,7 @@

    ### [11:00 - 12:30] Paul-Christian Bürkner

    - From classical GLMs to multi-level models
    - [From classical GLMs to multi-level model](https://github.com/InsuranceDataScience/StanWorkshop2018/blob/master/paul_buerkner/From_GLMs_to_MLMs.pdf)
    - Comparing classical GLMs with bayesian GLMs using rstanarm
    - Building more complex multi-level models using brms
    - Examples from pricing and claims reserving
    @@ -25,8 +25,8 @@
    ### [13:30 - 14:30] Mick Cooney & Jake Morris

    - Case studies from the insurance industry
    - Loss development curves in Stan (Mick Cooney)
    - Hierarchical compartmental reserving models (Jake Morris)
    - [Loss development curves in Stan](https://rawgit.com/InsuranceDataScience/StanWorkshop2018/master/loss_curves/loss_curves.html#/) (Mick Cooney)
    - [Hierarchical compartmental reserving models](https://rawgit.com/InsuranceDataScience/StanWorkshop2018/master/loss_curves/compart_models.html#/) (Jake Morris)

    ### [14:30 - 15:00] Coffee

  2. mages revised this gist Jul 4, 2018. 1 changed file with 9 additions and 7 deletions.
    16 changes: 9 additions & 7 deletions StanWorkshop2018.md
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    ## Stan in Insurance Workshop 17 July 2018

    #### [9:00 - 10:30] Eric Novik
    ### [8:30-9:00] Registration

    ### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    - Coding linear regression to assess wine quality
    @@ -9,26 +11,26 @@
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models

    #### [10:30 - 11:00] Coffee
    ### [10:30 - 11:00] Coffee

    #### [11:00 - 12:30] Paul-Christian Bürkner
    ### [11:00 - 12:30] Paul-Christian Bürkner

    - From classical GLMs to multi-level models
    - Comparing classical GLMs with bayesian GLMs using rstanarm
    - Building more complex multi-level models using brms
    - Examples from pricing and claims reserving

    #### [12:30 - 13:30] Lunch
    ### [12:30 - 13:30] Lunch

    #### [13:30 - 14:30] Mick Cooney & Jake Morris
    ### [13:30 - 14:30] Mick Cooney & Jake Morris

    - Case studies from the insurance industry
    - Loss development curves in Stan (Mick Cooney)
    - Hierarchical compartmental reserving models (Jake Morris)

    #### [14:30 - 15:00] Coffee
    ### [14:30 - 15:00] Coffee

    #### [15:00 - 17:00] Working in groups with support of the presenters
    ### [15:00 - 17:00] Working in groups with support of the presenters

    - Work on your own problems or work through on of the following examples:
    - [Loss curve case study (Mick Cooney)](http://mc-stan.org/users/documentation/case-studies/losscurves_casestudy.html)
  3. mages revised this gist May 4, 2018. 1 changed file with 14 additions and 14 deletions.
    28 changes: 14 additions & 14 deletions StanWorkshop2018.md
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    #### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models

    #### [10:30 - 11:00] Coffee

    #### [11:00 - 12:30] Paul-Christian Bürkner

    - From classical GLMs to multi-level models
    - Comparing classical GLMs with bayesian GLMs using rstanarm
    - Building more complex multi-level models using brms
    - Examples from pricing and claims reserving
    - Comparing classical GLMs with bayesian GLMs using rstanarm
    - Building more complex multi-level models using brms
    - Examples from pricing and claims reserving

    #### [12:30 - 13:30] Lunch

    #### [13:30 - 14:30] Mick Cooney & Jake Morris

    - Case studies from the insurance industry
    - Loss development curves in Stan (Mick Cooney)
    - Hierarchical compartmental reserving models (Jake Morris)
    - Loss development curves in Stan (Mick Cooney)
    - Hierarchical compartmental reserving models (Jake Morris)

    #### [14:30 - 15:00] Coffee

    #### [15:00 - 17:00] Working in groups with support of the presenters

    - Work on your own problems or work through on of the following examples:
    - [Loss curve case study (Mick Cooney)](http://mc-stan.org/users/documentation/case-studies/losscurves_casestudy.html)
    - [Extreme value case study (Aki Vehtari)](http://mc-stan.org/users/documentation/case-studies/gpareto_functions.html)
    - [Various insurance related examples from Markus Gesmann](https://magesblog.com/tags/stan/)
    - [Examples from the `brms` vignettes (Paul-Christian Bürkner)](https://CRAN.R-project.org/package=brms)
    - [Loss curve case study (Mick Cooney)](http://mc-stan.org/users/documentation/case-studies/losscurves_casestudy.html)
    - [Extreme value case study (Aki Vehtari)](http://mc-stan.org/users/documentation/case-studies/gpareto_functions.html)
    - [Various insurance related examples from Markus Gesmann](https://magesblog.com/tags/stan/)
    - [Examples from the `brms` vignettes (Paul-Christian Bürkner)](https://CRAN.R-project.org/package=brms)
  4. mages revised this gist May 4, 2018. 1 changed file with 6 additions and 6 deletions.
    12 changes: 6 additions & 6 deletions StanWorkshop2018.md
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    #### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    * Coding linear regression to assess wine quality
    * Demonstrating important parts of the Stan program
    * Doing some basic posterior predicting checking
    * Introduction to calibration and model comparison
    * Introduction to making decisions with Bayesian models
    - Intro to Stan, including:
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models

    #### [10:30 - 11:00] Coffee

  5. mages revised this gist May 4, 2018. 1 changed file with 5 additions and 5 deletions.
    10 changes: 5 additions & 5 deletions StanWorkshop2018.md
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    #### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models
    * Coding linear regression to assess wine quality
    * Demonstrating important parts of the Stan program
    * Doing some basic posterior predicting checking
    * Introduction to calibration and model comparison
    * Introduction to making decisions with Bayesian models

    #### [10:30 - 11:00] Coffee

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    0 StanWorkshop2018 → StanWorkshop2018.md
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  7. mages created this gist May 4, 2018.
    37 changes: 37 additions & 0 deletions StanWorkshop2018
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    ## Stan in Insurance Workshop 17 July 2018

    #### [9:00 - 10:30] Eric Novik

    - Intro to Stan, including:
    - Coding linear regression to assess wine quality
    - Demonstrating important parts of the Stan program
    - Doing some basic posterior predicting checking
    - Introduction to calibration and model comparison
    - Introduction to making decisions with Bayesian models

    #### [10:30 - 11:00] Coffee

    #### [11:00 - 12:30] Paul-Christian Bürkner

    - From classical GLMs to multi-level models
    - Comparing classical GLMs with bayesian GLMs using rstanarm
    - Building more complex multi-level models using brms
    - Examples from pricing and claims reserving

    #### [12:30 - 13:30] Lunch

    #### [13:30 - 14:30] Mick Cooney & Jake Morris

    - Case studies from the insurance industry
    - Loss development curves in Stan (Mick Cooney)
    - Hierarchical compartmental reserving models (Jake Morris)

    #### [14:30 - 15:00] Coffee

    #### [15:00 - 17:00] Working in groups with support of the presenters

    - Work on your own problems or work through on of the following examples:
    - [Loss curve case study (Mick Cooney)](http://mc-stan.org/users/documentation/case-studies/losscurves_casestudy.html)
    - [Extreme value case study (Aki Vehtari)](http://mc-stan.org/users/documentation/case-studies/gpareto_functions.html)
    - [Various insurance related examples from Markus Gesmann](https://magesblog.com/tags/stan/)
    - [Examples from the `brms` vignettes (Paul-Christian Bürkner)](https://CRAN.R-project.org/package=brms)