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easystats
parameters:Processing of Model Parameters
Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Maintained by Daniel Lüdecke. Last updated 10 days ago.
betabootstrapciconfidence-intervalsdata-reductioneasystatsfafeature-extractionfeature-reductionhacktoberfestparameterspcapvaluesregression-modelsrobust-statisticsstandardizestandardized-estimatesstatistical-models
454 stars 15.67 score 1.8k scripts 56 dependents
paulnorthrop
bang:Bayesian Analysis, No Gibbs
Provides functions for the Bayesian analysis of some simple commonly-used models, without using Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution, using the generalized ratio-of-uniforms method. See Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987> for details. At the moment three conjugate hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way analysis of variance (ANOVA).
Maintained by Paul J. Northrop. Last updated 2 months ago.
anovabayesianbetabinomialgammagibbshierarchicalpoisson
3 stars 5.62 score 35 scripts