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