rstan
MultiBUGS
| rstan | MultiBUGS | |
|---|---|---|
| 8 | 1 | |
| 1,008 | 30 | |
| 1.7% | - | |
| 7.7 | 0.0 | |
| 13 days ago | almost 3 years ago | |
| R | Shell | |
| - | GNU Lesser General Public License v3.0 only |
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rstan
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R packages in Colab - either speed up install, or import library?
I have a Colab notebook with an R kernel that I'm using to share with students for remote lessons in statistics. This notebook relies on "rstanarm", which is pretty massive with the number of dependencies - it takes ~50minutes to install into a fresh Colab session with install.packages(). It seems the issue is that many of the dependencies of this package need to be compiled from source, which takes a long time on Linux distributions like Colab.
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Help troubleshooting a an error in a brms Regression
You need to install the preview version of rstan: https://github.com/stan-dev/rstan/wiki/Configuring-C---Toolchain-for-Windows
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Time series tutorial series
If you're on Windows, there are extra hoop to jump through, I'm afraid https://github.com/stan-dev/rstan/wiki/
- [S] Pyro/Numpyro or Stan for Bayesian modeling?
- Why does rstan depend on V8?
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Help with error running stan model using brms package
And here are the instructions on how to build RStan from source: https://github.com/stan-dev/rstan/wiki
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trouble installing rstan on mac
I ran the R code from here
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Looking to do Bayesian two-way ANOVA - can someone point me in the right direction?
In R, the rstanarm package should do you well. You'll need to install rstan and make sure you have a C++ complier set up as well (instructions here: https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started)
MultiBUGS
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Project Oberon Emulator in JavaScript and Java
Oberon is awesome. I typically use a variant of it called Component Pascal. It is a very esoteric, and quite unique language.
My usage of it is in WinBUGS/OpenBUGS/MultiBUGS [1], for Markov chain Monte Carlo statistical analysis. It's really cool and works amazingly well for systems of differential equations too.
The version I recommend using is MultiBUGS [2]. I would avoid installing it in Windows, though!
[1] https://www.mrc-bsu.cam.ac.uk/software/bugs/
[2] https://github.com/MultiBUGS/MultiBUGS
What are some alternatives?
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
paramonte - ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
stan - Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
numpyro - Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
PyMC - Bayesian Modeling and Probabilistic Programming in Python
vroom - Fast reading of delimited files
security - Collection of CVEs from Sick Codes, or collaborations on https://sick.codes security research & advisories.
stanc3 - The Stan transpiler (from Stan to C++ and beyond).
r-macos-rtools - Scripts to build an **unofficial** Rtools-esq installer for the macOS R toolchain