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Boom (version 0.7)

Bayesian Object Oriented Modeling

Description

A C++ library for Bayesian modeling, with an emphasis on Markov chain Monte Carlo. Although boom contains a few R utilities (mainly plotting functions), its primary purpose is to install the BOOM C++ library on your system so that other packages can link against it.

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Version

Install

install.packages('Boom')

Monthly Downloads

2,253

Version

0.7

License

LGPL-2.1 | file LICENSE

Maintainer

Steven Scott

Last Published

May 28th, 2017

Functions in Boom (0.7)

ToString

Convert to Character String
add.segments

Function to add horizontal line segments to an existing plot
check.data

Checking data formats
compare.den

Compare several density estimates.
compare.dynamic.distributions

Compare Dynamic Distributions
compare.many.densities

Compare several density estimates.
ar1.coefficient.prior

Normal prior for an AR1 coefficient
beta.prior

Beta prior for a binomial proportion
boxplot.mcmc.matrix

Plot the distribution of a matrix
boxplot.true

side-by-side boxplots from a matrix, with optional reference values
dirichlet-distribution

The Dirichlet Distribution
dirichlet.prior

Dirichlet prior for a multinomial distribution
is.even

Check whether a number is even or odd.
lmgamma

Log Multivariate Gamma Function
gamma.prior

Gamma prior distribution
GenerateFactorData

Generate a data frame of all factor data
lognormal.prior

Lognormal Prior Distribution
markov.prior

Prior for a Markov chain
sufstat.Rd

Sufficient Statistics
suggest.burn.log.likelihood

Suggest MCMC Burn-in from Log Likelihood
compare.many.ts

Compares several density estimates.
compare.vector.distribution

Boxplots to compare distributions of vectors
match_data_frame

MatchDataFrame
mscan

Scan a Matrix
plot.dynamic.distribution

Plots the pointwise evolution of a distribution over an index set.
plot.macf

Plots individual autocorrelation functions for many-valued time series
uniform.prior

Uniform prior distribution
wishart

Wishart Distribution
mvn.prior

Multivariate normal prior
normal.inverse.gamma.prior

Normal inverse gamma prior
thin

Thin the rows of a matrix
plot.many.ts

Multiple time series plots
regression.coefficient.conjugate.prior

Regression Coefficient Conjugate Prior
double.model

Prior distributions for a real valued scalar
external.legend

Add an external legend to an array of plots.
mvn.diagonal.prior

diagonal MVN prior
mvn.independent.sigma.prior

Independence prior for the MVN
normal.inverse.wishart.prior

Normal inverse Wishart prior
normal.prior

Normal (scalar Gaussian) prior distribution
TimeSeriesBoxplot

Time Series Boxplots
discrete-uniform-prior

Discrete prior distributions
dmvn

Multivariate Normal Density
histabunch

A Bunch of Histograms
inverse-wishart

Inverse Wishart Distribution
thin.matrix

Thin a Matrix
traceproduct

Trace of the Product of Two Matrices
pairs.density

Pairs plot for posterior distributions.
plot.density.contours

Contour plot of a bivariate density.
rmvn

Multivariate Normal Simulation
sd.prior

Prior for a standard deviation or variance