brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan (by paul-buerkner)
BayesCog_Wien
Teaching materials for BayesCog at Faculty of Psychology, University of Vienna (by lei-zhang)
| brms | BayesCog_Wien | |
|---|---|---|
| 9 | 2 | |
| 1,292 | 141 | |
| 0.6% | - | |
| 9.3 | 0.0 | |
| about 1 month ago | over 3 years ago | |
| R | R | |
| GNU General Public License v3.0 only | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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] https://paul-buerkner.github.io/brms/
-
[Q] Correlated multivariate Beta model
Maybe something like the Logistic Normal ? (e.g. see this issue from brms). If that fits what you are looking for, you can use brms to generate the Stan code for you (brms::make_stan_code()) and work from that.
-
Step-by-step example of Bayesian t-test?
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?
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.
-
Package for :Generalized Mixed Effects Models for Zero-Inflated Negative Binomial distributions ?
brms baby
-
Multiple observers
Could also be done using brms and the gr term. See this for the motivation behind this syntax.
-
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?
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
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.
BayesCog_Wien
Posts with mentions or reviews of BayesCog_Wien.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-10.
What are some alternatives?
When comparing brms and BayesCog_Wien you can also consider the following projects:
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.
knitr_case_studies - Inference case studies in knitr
rstan - RStan, the R interface to Stan
EpiNow2 - Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
bambi - BAyesian Model-Building Interface (Bambi) in Python.
bayescogsci - Draft of book entitled An Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, Vasishth
tinytex - A lightweight, cross-platform, portable, and easy-to-maintain LaTeX distribution based on TeX Live
RTutorials - A set of tutorials for using R in various ways: for coding and statistics
tests-as-linear - Common statistical tests are linear models (or: how to teach stats)
jaspLearnBayes - A module to help learn bayesian statistics
rBAPS - R implementation of the BAPS software for Bayesian Analysis of Population Structure
CognitiveModelingWorkshop - Workshop on Mathematical Modeling of Cognitive Processes