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bayes-rules

bayesrules:Datasets and Supplemental Functions from Bayes Rules! Book

Provides datasets and functions used for analysis and visualizations in the Bayes Rules! book (<https://www.bayesrulesbook.com>). The package contains a set of functions that summarize and plot Bayesian models from some conjugate families and another set of functions for evaluation of some Bayesian models.

Maintained by Mine Dogucu. Last updated 3 years ago.

bayesian-statisticsdata

70 stars 8.01 score 466 scripts

philipberg

baldur:Bayesian Hierarchical Modeling for Label-Free Proteomics

Statistical decision in proteomics data using a hierarchical Bayesian model. There are two regression models for describing the mean-variance trend, a gamma regression or a latent gamma mixture regression. The regression model is then used as an Empirical Bayes estimator for the prior on the variance in a peptide. Further, it assumes that each measurement has an uncertainty (increased variance) associated with it that is also inferred. Finally, it tries to estimate the posterior distribution (by Hamiltonian Monte Carlo) for the differences in means for each peptide in the data. Once the posterior is inferred, it integrates the tails to estimate the probability of error from which a statistical decision can be made. See Berg and Popescu for details (<doi:10.1101/2023.05.11.540411>).

Maintained by Philip Berg. Last updated 8 months ago.

cpp

1 stars 4.00 score 8 scripts

tk382

MMVBVS:Missing Multivariate Bayesian Variable Selection

A variable selection tool for multivariate normal variables with missing-at-random values using Bayesian Hierarchical Model. Visualization functions show the posterior distribution of gamma (inclusion variables) and beta (coefficients). Users can also visualize the heatmap of the posterior mean of covariance matrix. Kim, T. Nicolae, D. (2019)<https://github.com/tk382/MMVBVS/blob/master/workingpaper.pdf>. Guan, Y. Stephens, M. (2011)<doi:10.1214/11-AOAS455>.

Maintained by Tae Kim. Last updated 5 years ago.

openblascpp

2.70 score

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