Brms Alternatives

brms reviews and mentions

• Bayesian Structural Equation Modeling using blavaan
  2 projects | news.ycombinator.com | 9 Nov 2023

  [2] https://paul-buerkner.github.io/brms/

• [Q] Correlated multivariate Beta model
  1 project | /r/statistics | 9 Jun 2022

  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?
  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.

• Package for :Generalized Mixed Effects Models for Zero-Inflated Negative Binomial distributions ?
  1 project | /r/rstats | 30 Jul 2021

  brms baby

• Multiple observers
  1 project | /r/AskStatistics | 16 Jul 2021

  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?
  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.

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