MCMCpack v1.4-9
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Markov Chain Monte Carlo (MCMC) Package
Contains functions to perform Bayesian
inference using posterior simulation for a number of
statistical models. Most simulation is done in compiled C++
written in the Scythe Statistical Library Version 1.0.3. All
models return 'coda' mcmc objects that can then be summarized
using the 'coda' package. Some useful
utility functions such as density functions,
pseudo-random number generators for statistical
distributions, a general purpose Metropolis sampling algorithm,
and tools for visualization are provided.
Functions in MCMCpack
| Name | Description | |
| HMMpanelRE | Markov Chain Monte Carlo for the Hidden Markov Random-effects Model | |
| InvGamma | The Inverse Gamma Distribution | |
| InvWishart | The Inverse Wishart Distribution | |
| MCMCSVDreg | Markov Chain Monte Carlo for SVD Regression | |
| HDPHSMMnegbin | Markov Chain Monte Carlo for HDP-HSMM with a Negative Binomial outcome distribution | |
| HMMpanelFE | Markov Chain Monte Carlo for the Hidden Markov Fixed-effects Model | |
| HDPHMMpoisson | Markov Chain Monte Carlo for sticky HDP-HMM with a Poisson outcome distribution | |
| HDPHMMnegbin | Markov Chain Monte Carlo for sticky HDP-HMM with a Negative Binomial outcome distribution | |
| Dirichlet | The Dirichlet Distribution | |
| BayesFactor | Create an object of class BayesFactor from MCMCpack output | |
| MCMCbinaryChange | Markov Chain Monte Carlo for a Binary Multiple Changepoint Model | |
| MCMCirtHier1d | Markov Chain Monte Carlo for Hierarchical One Dimensional Item Response Theory Model, Covariates Predicting Latent Ideal Point (Ability) | |
| MCMCdynamicIRT1d_b | Markov Chain Monte Carlo for Dynamic One Dimensional Item Response Theory Model | |
| MCMCirt1d | Markov Chain Monte Carlo for One Dimensional Item Response Theory Model | |
| MCMChierEI | Markov Chain Monte Carlo for Wakefield's Hierarchial Ecological Inference Model | |
| MCMChregress | Markov Chain Monte Carlo for the Hierarchical Gaussian Linear Regression Model | |
| MCMChpoisson | Markov Chain Monte Carlo for the Hierarchical Poisson Linear Regression Model using the log link function | |
| MCMCdynamicEI | Markov Chain Monte Carlo for Quinn's Dynamic Ecological Inference Model | |
| MCMChlogit | Markov Chain Monte Carlo for the Hierarchical Binomial Linear Regression Model using the logit link function | |
| MCMCfactanal | Markov Chain Monte Carlo for Normal Theory Factor Analysis Model | |
| MCMCnegbin | Markov Chain Monte Carlo for Negative Binomial Regression | |
| MCMCmixfactanal | Markov Chain Monte Carlo for Mixed Data Factor Analysis Model | |
| MCMCoprobit | Markov Chain Monte Carlo for Ordered Probit Regression | |
| MCMCmnl | Markov Chain Monte Carlo for Multinomial Logistic Regression | |
| MCMCirtKdRob | Markov Chain Monte Carlo for Robust K-Dimensional Item Response Theory Model | |
| MCMCmetrop1R | Metropolis Sampling from User-Written R function | |
| MCMCoprobitChange | Markov Chain Monte Carlo for Ordered Probit Changepoint Regression Model | |
| MCMCnegbinChange | Markov Chain Monte Carlo for Negative Binomial Regression Changepoint Model | |
| MCMClogit | Markov Chain Monte Carlo for Logistic Regression | |
| MCMCresidualBreakAnalysis | Break Analysis of Univariate Time Series using Markov Chain Monte Carlo | |
| MCMCirtKd | Markov Chain Monte Carlo for K-Dimensional Item Response Theory Model | |
| MCMCordfactanal | Markov Chain Monte Carlo for Ordinal Data Factor Analysis Model | |
| MCMCregress | Markov Chain Monte Carlo for Gaussian Linear Regression | |
| MCMCregressChange | Markov Chain Monte Carlo for a linear Gaussian Multiple Changepoint Model | |
| MCMCquantreg | Bayesian quantile regression using Gibbs sampling | |
| PErisk | Political Economic Risk Data from 62 Countries in 1987 | |
| MCMCprobit | Markov Chain Monte Carlo for Probit Regression | |
| PostProbMod | Calculate Posterior Probability of Model | |
| Rehnquist | U.S. Supreme Court Vote Matrix, Rehnquist Court (1994-2004) | |
| MCMCprobitChange | Markov Chain Monte Carlo for a linear Gaussian Multiple Changepoint Model | |
| plotChangepoint | Posterior Density of Regime Change Plot | |
| MCMCpoissonChange | Markov Chain Monte Carlo for a Poisson Regression Changepoint Model | |
| MCnormalnormal | Monte Carlo Simulation from a Normal Likelihood (with known variance) with a Normal Prior | |
| MCbinomialbeta | Monte Carlo Simulation from a Binomial Likelihood with a Beta Prior | |
| MCMCpoisson | Markov Chain Monte Carlo for Poisson Regression | |
| SSVSquantreg | Stochastic search variable selection for quantile regression | |
| plotHDPChangepoint | Posterior Changepoint Probabilities from HDP-HMM | |
| MCmultinomdirichlet | Monte Carlo Simulation from a Multinomial Likelihood with a Dirichlet Prior | |
| read.Scythe | Read a Matrix from a File written by Scythe | |
| summaryqrssvs | Summarising the results of quantile regression stochastic search variable selection (QR-SSVS). | |
| plot.qrssvs | Plot output from quantile regression stochastic search variable selection (QR-SSVS). | |
| SupremeCourt | U.S. Supreme Court Vote Matrix | |
| Senate | 106th U.S. Senate Roll Call Vote Matrix | |
| mptable | Calculate the marginal posterior probabilities of predictors being included in a quantile regression model. | |
| testpanelGroupBreak | A Test for the Group-level Break using a Multivariate Linear Regression Model with Breaks | |
| xpnd | Expand a Vector into a Symmetric Matrix | |
| testpanelSubjectBreak | A Test for the Subject-level Break using a Unitivariate Linear Regression Model with Breaks | |
| MCMCtobit | Markov Chain Monte Carlo for Gaussian Linear Regression with a Censored Dependent Variable | |
| Nethvote | Dutch Voting Behavior in 1989 | |
| tomogplot | Tomography Plot | |
| topmodels | Shows an ordered list of the most frequently visited models sampled during quantile regression stochastic search variable selection (QR-SSVS). | |
| choicevar | Handle Choice-Specific Covariates in Multinomial Choice Models | |
| Wishart | The Wishart Distribution | |
| MCpoissongamma | Monte Carlo Simulation from a Poisson Likelihood with a Gamma Prior | |
| NoncenHypergeom | The Noncentral Hypergeometric Distribution | |
| vech | Extract Lower Triangular Elements from a Symmetric Matrix | |
| dtomogplot | Dynamic Tomography Plot | |
| make.breaklist | Vector of break numbers | |
| write.Scythe | Write a Matrix to a File to be Read by Scythe | |
| procrustes | Procrustes Transformation | |
| plotState | Changepoint State Plot | |
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Details
| Date | 2020-08-02 |
| License | GPL-3 |
| SystemRequirements | gcc (>= 4.0) |
| URL | https://CRAN.R-project.org/package=MCMCpack |
| Packaged | 2020-08-02 15:18:52 UTC; park |
| NeedsCompilation | yes |
| Repository | CRAN |
| RoxygenNote | 7.1.1 |
| Encoding | UTF-8 |
| Date/Publication | 2020-08-02 17:30:02 UTC |
| depends | coda (>= 0.11-3) , MASS , R (>= 3.6) , stats |
| imports | graphics , grDevices , lattice , mcmc , methods , quantreg , utils |
| Contributors | Andrew Martin, Ben Goodrich, Ghislain Vieilledent, Michael Malecki, Kevin Quinn, Ross Ihaka, Pierre L'Ecuyer, The Development Core Team, Jong Park, Matthew Blackwell, The Foundation, Makoto Matsumoto, Takuji Nishimura, Keith Poole, Craig Reed |
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