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bayesSurv (version 2.4)
Bayesian Survival Regression with Flexible Error and Random Effects Distributions
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Install
install.packages('bayesSurv')
Monthly Downloads
243
Version
2.4
License
GPL (>= 2)
Maintainer
Arnošt Komárek
Last Published
February 5th, 2015
Functions in bayesSurv (2.4)
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bayessurvreg1.files2init
Read the initial values for the Bayesian survival regression model to the list.
bayesHistogram
Smoothing of a uni- or bivariate histogram using Bayesian G-splines
bayessurvreg1
A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components
densplot2
Probability density function estimate from MCMC output
bayessurvreg1.help
Helping function for Bayesian survival regression models, version 1.
give.summary
Brief summary for the chain(s) obtained using the MCMC.
bayesDensity
Summary for the density estimate based on the mixture Bayesian AFT model.
credible.region
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
bayesBisurvreg.help
Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data
plot.bayesGspline
Plot an object of class bayesGspline
bayesHistogram.help
Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
plot.marginal.bayesGspline
Plot an object of class marginal.bayesGspline
scanFN
Read Data Values
bayessurvreg3.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
predictive
Compute predictive quantities based on a Bayesian survival regression model fitted using bayessurvreg1 function.
predictive2
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate model with Bayesian G-splines.
cgd
Chronic Granulomatous Disease data
files2coda
Read the sampled values from the Bayesian survival regression model to a coda mcmc object.
bayesGspline
Summary for the density estimate based on the model with Bayesian G-splines.
tandmob2
Signal Tandmobiel data, version 2
bayessurvreg3
Cluster-specific accelerated failure time model for multivariate, possibly doubly-interval-censored data with flexibly specified random effects and/or error distribution.
rWishart
Sample from the Wishart distribution
rMVNorm
Sample from the multivariate normal distribution
tandmobRoos
Signal Tandmobiel data, version Roos
vecr2matr
Transform single component indeces to double component indeces
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.
bayessurvreg.help
Helping function for Bayesian survival regression models.
simult.pvalue
Compute a simultaneous p-value from a sample for a vector valued parameter.
files.Gspline
Write headers to or clean files with sampled G-spline
print.bayesDensity
Print a summary for the density estimate based on the Bayesian model.
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).
sampled.kendall.tau
Estimate of the Kendall's tau from the bivariate model
traceplot2
Trace plot of MCMC output.
sampleCovMat
Compute a sample covariance matrix.
plot.bayesDensity
Plot an object of class bayesDensity
bayessurvreg2.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
give.init
Check and possibly fill in initial values for the G-spline, augmented observations and allocations for Bayesian models with G-splines