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bayesSurv (version 0.4-1)
Bayesian Survival Regression with Flexible Error and Random Effects Distributions
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Install
install.packages('bayesSurv')
Monthly Downloads
243
Version
0.4-1
License
GPL version 2 or newer
Maintainer
Arnost Komarek
Last Published
September 16th, 2024
Functions in bayesSurv (0.4-1)
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bayesHistogram
Smoothing of a uni- or bivariate histogram using Bayesian G-splines
vecr2matr
Transform single component indeces to double component indeces
bayesBisurvreg.help
Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data
bayesHistogram.help
Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
bayessurvreg3.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
sampled.kendall.tau
Estimate of the Kendall's tau from the bivariate model
give.init
Check and possibly fill in initial values for the G-spline, augmented observations and allocations for Bayesian models with G-splines
print.bayesDensity
Print a summary for the density estimate based on the Bayesian model.
predictive2
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
bayesDensity
Summary for the density estimate based on the mixture Bayesian AFT model.
bayessurvreg3
Cluster-specific accelerated failure time model for multivariate, possibly doubly-interval-censored data. The random intercept can be included in the model formula. Both the error distribution and the distribution of the random intercept is expressed as a~penalized univariate normal mixture with high number of components (G-spline).
plot.marginal.bayesGspline
Plot an object of class marginal.bayesGspline
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.
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).
bayessurvreg.help
Helping function for Bayesian survival regression models.
bayessurvreg1.help
Helping function for Bayesian survival regression models, version 1.
credible.region
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
bayessurvreg2.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
cgd
Chronic Granulomatous Disease data
files.Gspline
Write headers to or clean files with sampled G-spline
sampleCovMat
Compute a sample covariance matrix.
give.summary
Brief summary for the chain(s) obtained using the MCMC.
plot.bayesDensity
Plot an object of class bayesDensity
tandmobRoos
Signal Tandmobiel data, version Roos
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.
tandmob2
Signal Tandmobiel data, version 2
plot.bayesGspline
Plot an object of class bayesGspline
traceplot2
Trace plot of MCMC output.
marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate model with Bayesian G-splines.
simult.pvalue
Compute a simultaneous p-value from a sample for a vector valued parameter.
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
files2coda
Read the sampled values from the Bayesian survival regression model to a coda mcmc object.