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BayesSUR (version 1.2-0)

Bayesian Seemingly Unrelated Regression

Description

Bayesian seemingly unrelated regression with general variable selection and dense/sparse covariance matrix. The sparse seemingly unrelated regression is described in Banterle et al. (2018) .

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Version

Install

install.packages('BayesSUR')

Monthly Downloads

372

Version

1.2-0

License

MIT + file LICENSE

Maintainer

Zhi Zhao

Last Published

July 2nd, 2020

Functions in BayesSUR (1.2-0)

get.estimator

extract the posterior mean of the parameters

fitted.BayesSUR

fitted response values corresponds to the posterior mean estimates

BayesSUR_internal

BayesSUR

main function of the package

example_GDSC

Preprocessed data set to mimic a small pharmacogenetic example

example_eQTL

Simulated data set to mimic a small expression quantitative trait loci (eQTL) example

plot.response.graph

plot the estimated graph for multiple response variables

print.BayesSUR

print a short summary of the Bayesian Seemingly Unrelated Regressions Fits

plot.MCMCdiag

show trace plots and diagnostic density plots

plot.Manhattan

plot Manhattan-like plots for marginal posterior inclusion probabilities (mPIP) and numbers of responses of association for predictors

summary.BayesSUR

summarizing Bayesian Seemingly Unrelated Regressions Fits

elpd

measure the prediction accuracy by the expected log pointwise predictive density

coef.BayesSUR

extract the posterior mean of the coefficients of a "BayesSUR" class object

predict.BayesSUR

predict responses corresponding to the posterior mean of the coefficients, return posterior mean of coefficients or indices of nonzero coefficients

plot.network

plot the network representation of the associations between responses and predictors

plot.estimator

plot the posterior mean estimators

plot.BayesSUR

create a selection of plots for a "BayesSUR" class object

plot.CPO

plot the conditional predictive ordinate

targetGene