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Jonah Sol Gabry · statistician

The new rstanarm R package. This post by Andrew Gelman first appeared on Statistical Modeling, Causual Inference, and Social Science. The files in its. Subdirectory, which can be called via the demo() function, show how you can fit essentially all of the models in Gelman and Hill’s textbook. Already offers more (although not strictly a superset of the) functionality in the arm. Package can be installed in the usual way with. However, the vignettes on the CRAN website. Does and how it works. But add regul...

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Jonah Sol Gabry · statistician | jgabry.github.io Reviews

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The new rstanarm R package. This post by Andrew Gelman first appeared on Statistical Modeling, Causual Inference, and Social Science. The files in its. Subdirectory, which can be called via the demo() function, show how you can fit essentially all of the models in Gelman and Hill’s textbook. Already offers more (although not strictly a superset of the) functionality in the arm. Package can be installed in the usual way with. However, the vignettes on the CRAN website. Does and how it works. But add regul...

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Jonah Sol Gabry · statistician | jgabry.github.io Reviews

https://jgabry.github.io

The new rstanarm R package. This post by Andrew Gelman first appeared on Statistical Modeling, Causual Inference, and Social Science. The files in its. Subdirectory, which can be called via the demo() function, show how you can fit essentially all of the models in Gelman and Hill’s textbook. Already offers more (although not strictly a superset of the) functionality in the arm. Package can be installed in the usual way with. However, the vignettes on the CRAN website. Does and how it works. But add regul...

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jgabry.github.io

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Introducing shinyStan · Jonah Sol Gabry

http://jgabry.github.io/2015/03/19/introducing-shinystan

This post first appeared on Statistical Modeling, Causual Inference, and Social Science. As a project for Andrew's Statistical Communication and Graphics graduate course. The result is shinyStan. A package for R and an app powered by Shiny. The full version of shinyStan v1.0.0 can be downloaded as an R package from the Stan Development Team GitHub page here. And we have a demo up online here. If you're not an R user, we're working on a full online version of shinyStan too. 2) Convenient saving and sharing.

2

About · Jonah Sol Gabry

http://jgabry.github.io/about

Statistician at Columbia University and Stan.

3

ShinyStan v2.0.0 · Jonah Sol Gabry

http://jgabry.github.io/2015/08/11/shinystan-version-2

ShinyStan v2.0.0. Img src= https:/ raw.githubusercontent.com/stan-dev/logos/master/logo.png width=200 alt= Stan Logo /. ShinyStan v2.0.0. Provides immediate, informative, customizable visual and numerical summaries of model parameters and convergence diagnostics for MCMC simulations. The ShinyStan graphical user interface is available via the shinystan R package. Try the online demo. Installing the shinystan R package. If this fails, try adding the arguments. Repos='http:/ cran.rstudio.com'. The shinysta...

4

The new rstanarm R package · Jonah Sol Gabry

http://jgabry.github.io/2016/01/29/introducing-rstanarm

The new rstanarm R package. This post by Andrew Gelman first appeared on Statistical Modeling, Causual Inference, and Social Science. The files in its. Subdirectory, which can be called via the demo() function, show how you can fit essentially all of the models in Gelman and Hill’s textbook. Already offers more (although not strictly a superset of the) functionality in the arm. Package can be installed in the usual way with. However, the vignettes on the CRAN website. Does and how it works. But add regul...

5

Software & Papers · Jonah Sol Gabry

http://jgabry.github.io/software

Statistical modeling language and inference algorithms for full Bayesian inference, approximate Bayesian inference, and penalized maximum likelihood estimation. Source code on GitHub. Source code on GitHub. An R package providing tools for developing R packages interfacing with Stan. Source code on GitHub. Bayesian Applied Regression Modeling via Stan. The rstanarm. Package is an appendage to the rstan. Source code on GitHub. Source code on GitHub. Source code on GitHub. Source code on GitHub.

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Design, doc, code and test. Stan is a team effort that could not be carried out without the generous support. Of grants, foundations, sponsors, and volunteer developers. Core Developers (in order of joining). Adobe Creative Technologies Lab. University of Toronto, Scarborough. University of São Paulo/UFSCar. Stan Group, Columbia University. Consultant, La Jolla, California. Robert L. Grant. St George's, University of London and Kingston University. University of Massachusetts, Amherst.

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Jonah Sol Gabry · statistician

The new rstanarm R package. This post by Andrew Gelman first appeared on Statistical Modeling, Causual Inference, and Social Science. The files in its. Subdirectory, which can be called via the demo() function, show how you can fit essentially all of the models in Gelman and Hill’s textbook. Already offers more (although not strictly a superset of the) functionality in the arm. Package can be installed in the usual way with. However, the vignettes on the CRAN website. Does and how it works. But add regul...

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