Showing 7 of total 7 results (show query)
laplacesdemonr
LaplacesDemon:Complete Environment for Bayesian Inference
Provides a complete environment for Bayesian inference using a variety of different samplers (see ?LaplacesDemon for an overview).
Maintained by Henrik Singmann. Last updated 1 years ago.
93 stars 13.45 score 1.8k scripts 60 dependents
twolodzko
extraDistr:Additional Univariate and Multivariate Distributions
Density, distribution function, quantile function and random generation for a number of univariate and multivariate distributions. This package implements the following distributions: Bernoulli, beta-binomial, beta-negative binomial, beta prime, Bhattacharjee, Birnbaum-Saunders, bivariate normal, bivariate Poisson, categorical, Dirichlet, Dirichlet-multinomial, discrete gamma, discrete Laplace, discrete normal, discrete uniform, discrete Weibull, Frechet, gamma-Poisson, generalized extreme value, Gompertz, generalized Pareto, Gumbel, half-Cauchy, half-normal, half-t, Huber density, inverse chi-squared, inverse-gamma, Kumaraswamy, Laplace, location-scale t, logarithmic, Lomax, multivariate hypergeometric, multinomial, negative hypergeometric, non-standard beta, normal mixture, Poisson mixture, Pareto, power, reparametrized beta, Rayleigh, shifted Gompertz, Skellam, slash, triangular, truncated binomial, truncated normal, truncated Poisson, Tukey lambda, Wald, zero-inflated binomial, zero-inflated negative binomial, zero-inflated Poisson.
Maintained by Tymoteusz Wolodzko. Last updated 24 days ago.
c-plus-plusc-plus-plus-11distributionmultivariate-distributionsprobabilityrandom-generationrcppstatisticscpp
53 stars 11.60 score 1.5k scripts 107 dependents
dmphillippo
multinma:Bayesian Network Meta-Analysis of Individual and Aggregate Data
Network meta-analysis and network meta-regression models for aggregate data, individual patient data, and mixtures of both individual and aggregate data using multilevel network meta-regression as described by Phillippo et al. (2020) <doi:10.1111/rssa.12579>. Models are estimated in a Bayesian framework using 'Stan'.
Maintained by David M. Phillippo. Last updated 3 days ago.
35 stars 9.34 score 163 scripts
poissonconsulting
extras:Helper Functions for Bayesian Analyses
Functions to 'numericise' 'R' objects (coerce to numeric objects), summarise 'MCMC' (Monte Carlo Markov Chain) samples and calculate deviance residuals as well as 'R' translations of some 'BUGS' (Bayesian Using Gibbs Sampling), 'JAGS' (Just Another Gibbs Sampler), 'STAN' and 'TMB' (Template Model Builder) functions.
Maintained by Nicole Hill. Last updated 2 months ago.
9 stars 8.49 score 15 scripts 16 dependents
paulponcet
statip:Statistical Functions for Probability Distributions and Regression
A collection of miscellaneous statistical functions for probability distributions: 'dbern()', 'pbern()', 'qbern()', 'rbern()' for the Bernoulli distribution, and 'distr2name()', 'name2distr()' for distribution names; probability density estimation: 'densityfun()'; most frequent value estimation: 'mfv()', 'mfv1()'; other statistical measures of location: 'cv()' (coefficient of variation), 'midhinge()', 'midrange()', 'trimean()'; construction of histograms: 'histo()', 'find_breaks()'; calculation of the Hellinger distance: 'hellinger()'; use of classical kernels: 'kernelfun()', 'kernel_properties()'; univariate piecewise-constant regression: 'picor()'.
Maintained by Paul Poncet. Last updated 5 years ago.
2 stars 7.17 score 73 scripts 52 dependents
cran
mc2d:Tools for Two-Dimensional Monte-Carlo Simulations
A complete framework to build and study Two-Dimensional Monte-Carlo simulations, aka Second-Order Monte-Carlo simulations. Also includes various distributions (pert, triangular, Bernoulli, empirical discrete and continuous).
Maintained by Regis Pouillot. Last updated 10 months ago.
1 stars 6.28 score 16 dependentscran
Rlab:Functions and Datasets Required for ST370 Class
Provides functions and datasets required for the ST 370 course at North Carolina State University.
Maintained by Dennis Boos. Last updated 3 years ago.
2.42 score 8 dependents