R bayesian-inference Projects
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Project mention: [R] Are there methods for ridge and lasso regression that allow the introduction of weights to give more importance to some observations? | reddit.com/r/MachineLearning | 2021-08-23
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.
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Project mention: [D] Selecting Hyperparameters Using Bayesian Optimization | reddit.com/r/statistics | 2021-03-03
Disclaimer: I am the maintainer of ParBayesianOptimization. That readme has a pretty good walkthrough of how Bayesian optimization works.
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Scout APM
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R bayesian-inference related posts
- [R] Are there methods for ridge and lasso regression that allow the introduction of weights to give more importance to some observations?
- Package for :Generalized Mixed Effects Models for Zero-Inflated Negative Binomial distributions ?
- Multiple observers
- 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?
- [D] Machine Learning and "Record Linkage"
- [D] Selecting Hyperparameters Using Bayesian Optimization
- Brms: adding on a nonlinear component to working MLM model
Index
| Project | Stars | |
|---|---|---|
| 1 | brms | 953 |
| 2 | ParBayesianOptimization | 73 |
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