BTM
rstan
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BTM
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best text mining packages?
For brief description you can refer to the BTM repo. If you want to go into detail just read the paper on BTM which is also linked there. Otherwise i strongly suggest you to keep things tidy/stick with tidytext.
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)
What are some alternatives?
quanteda - An R package for the Quantitative Analysis of Textual Data
brms - brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
vroom - Vehicle Routing Open-source Optimization Machine
MultiBUGS - Multi-core BUGS for fast Bayesian inference of large hierarchical models
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.
paramonte - ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
Rcpp - Seamless R and C++ Integration
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.
readxl - Read excel files (.xls and .xlsx) into R 🖇
vroom - Fast reading of delimited files
stanc3 - The Stan transpiler (from Stan to C++ and beyond).