brms VS stan

Compare brms vs stan and see what are their differences.

brms

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan (by paul-buerkner)

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. (by stan-dev)
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brms stan
9 44
1,224 2,504
- 0.8%
9.3 9.5
6 days ago 7 days ago
R C++
GNU General Public License v3.0 only BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

brms

Posts with mentions or reviews of brms. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-11-09.
  • Bayesian Structural Equation Modeling using blavaan
    2 projects | news.ycombinator.com | 9 Nov 2023
    [2] https://paul-buerkner.github.io/brms/
  • Step-by-step example of Bayesian t-test?
    4 projects | /r/AskStatistics | 3 Apr 2022
    Okay so first off, I recommend that you read [this](https://link.springer.com/article/10.3758/s13423-016-1221-4) article about "The Bayesian New Statistics", which highlights estimation rather than hypothesis testing from a Bayesian perspective (see Fig. 1, second row, second column). Instead of a t-test, then, we can *estimate the difference* between two groups/variables. If you want to go deeper than JASP etc, I recommend that you use [brms](https://paul-buerkner.github.io/brms/), or, if you want to go even deeper, [Stan](https://mc-stan.org/) (brms is a front-end to Stan).
  • [R] Are there methods for ridge and lasso regression that allow the introduction of weights to give more importance to some observations?
    2 projects | /r/MachineLearning | 23 Aug 2021
    I think the brms package (https://github.com/paul-buerkner/brms) or the blavaan package (http://ecmerkle.github.io/blavaan/) have support for SEM. I've never done it myself, so I unfortunately can't give you any direction for that in particular. However, I have used stan in multi-level meta-analysis regression (combining multiple CRISPRa experiments to find determinants of CRISPRa activity, see https://github.com/timydaley/CRISPRa-sgRNA-determinants/blob/master/metaAnalysis/NeuronAndSelfRenewalMetaMixtureRegression.Rmd) and had some success.
  • I have a small sample size time series with potentially lagged predictor values which are also time series. What could be potential methods to analyse these data?
    3 projects | /r/AskStatistics | 25 Apr 2021
    Anyway, I found I can include weights into the brm function by using gr(RE, by = var) to deal with the heterogeneous variance and it should automatically assume that each observation within a group is correlated according to the brms reference manual.
  • Brms: adding on a nonlinear component to working MLM model
    2 projects | /r/AskStatistics | 28 Feb 2021
    This is what actually should work- I must be declaring my variables incorrectly. The issue I'm having is that what you refer to as lin , I tried calling a few things, from b to LinPred (which worked in the link here: brms issue 47). When I've tried doing this, I receive errors that say "The following variables are missing from the dataset....[insert variable used to symbolize linear part of the model)". But I believe you're code is on the right path for what needs to be done- I'll try altering my syntax to be sure it resembles yours let you know if it works.
    2 projects | /r/AskStatistics | 28 Feb 2021
    Unfortunately, I can't just tag it onto to the working linear piece because brms doesn't allow for more than 2 level factor covariates in NL formulas. After much googling, I was able to find these brms github posts: 46 47 where they discuss how a NL component can be added. I've tried the syntax used, but it's still throwing errors. Here is one syntax I tried, going off of the information on those two links (where b1=lambda, b2= kappa)

stan

Posts with mentions or reviews of stan. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-08-14.

What are some alternatives?

When comparing brms and stan you can also consider the following projects:

PyMC - Bayesian Modeling and Probabilistic Programming in Python

jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

rstan - RStan, the R interface to Stan

Elo-MMR - Skill estimation systems for multiplayer competitions

probability - Probabilistic reasoning and statistical analysis in TensorFlow

tinytex - A lightweight, cross-platform, portable, and easy-to-maintain LaTeX distribution based on TeX Live

pyro - Deep universal probabilistic programming with Python and PyTorch

stat_rethinking_2020 - Statistical Rethinking Course Winter 2020/2021

MultiBUGS - Multi-core BUGS for fast Bayesian inference of large hierarchical models

fastbaps - A fast approximation to a Dirichlet Process Mixture model (DPM) for clustering genetic data

arviz - Exploratory analysis of Bayesian models with Python