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bayesSurv (version 0.5-9)
Bayesian Survival Regression with Flexible Error and Random Effects Distributions
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Install
install.packages('bayesSurv')
Monthly Downloads
243
Version
0.5-9
License
GPL version 2 or newer
Maintainer
Arnost Komarek
Last Published
September 16th, 2024
Functions in bayesSurv (0.5-9)
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bayessurvreg1.help
Helping function for Bayesian survival regression models, version 1.
bayesHistogram.help
Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
bayesBisurvreg
Population-averaged accelerated failure time model for bivariate, possibly doubly-interval-censored data. The error distribution is expressed as a~penalized bivariate normal mixture with high number of components (bivariate G-spline).
bayesDensity
Summary for the density estimate based on the mixture Bayesian AFT model.
bayesBisurvreg.help
Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data
bayessurvreg.help
Helping function for Bayesian survival regression models.
bayessurvreg1.files2init
Read the initial values for the Bayesian survival regression model to the list.
densplot2
Probability density function estimate from MCMC output
bayessurvreg1
A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components
bayessurvreg2.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
bayesGspline
Summary for the density estimate based on the model with Bayesian G-splines.
bayessurvreg3
Cluster-specific accelerated failure time model for multivariate, possibly doubly-interval-censored data with flexibly specified random effects and/or error distribution.
bayessurvreg2
Cluster-specific accelerated failure time model for multivariate, possibly doubly-interval-censored data. The error distribution is expressed as a~penalized univariate normal mixture with high number of components (G-spline). The distribution of the vector of random effects is multivariate normal.
predictive
Compute predictive quantities based on a Bayesian survival regression model fitted using bayessurvreg1 function.
give.summary
Brief summary for the chain(s) obtained using the MCMC.
scanFN
Read Data Values
files2coda
Read the sampled values from the Bayesian survival regression model to a coda mcmc object.
vecr2matr
Transform single component indeces to double component indeces
sampleCovMat
Compute a sample covariance matrix.
plot.bayesGspline
Plot an object of class bayesGspline
plot.marginal.bayesGspline
Plot an object of class marginal.bayesGspline
marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate model with Bayesian G-splines.
tandmob2
Signal Tandmobiel data, version 2
bayessurvreg3.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
tandmobRoos
Signal Tandmobiel data, version Roos
traceplot2
Trace plot of MCMC output.
credible.region
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
give.init
Check and possibly fill in initial values for the G-spline, augmented observations and allocations for Bayesian models with G-splines
simult.pvalue
Compute a simultaneous p-value from a sample for a vector valued parameter.
cgd
Chronic Granulomatous Disease data
bayesHistogram
Smoothing of a uni- or bivariate histogram using Bayesian G-splines
sampled.kendall.tau
Estimate of the Kendall's tau from the bivariate model
rMVNorm
Sample from the multivariate normal distribution
plot.bayesDensity
Plot an object of class bayesDensity
print.bayesDensity
Print a summary for the density estimate based on the Bayesian model.
files.Gspline
Write headers to or clean files with sampled G-spline
predictive2
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
rWishart
Sample from the Wishart distribution