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bayesSurv (version 0.5-7)
Bayesian Survival Regression with Flexible Error and Random Effects Distributions
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Install
install.packages('bayesSurv')
Monthly Downloads
616
Version
0.5-7
License
GPL version 2 or newer
Maintainer
Arnost Komarek
Last Published
May 29th, 2007
Functions in bayesSurv (0.5-7)
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bayessurvreg.help
Helping function for Bayesian survival regression models.
bayesHistogram
Smoothing of a uni- or bivariate histogram using Bayesian G-splines
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).
bayesBisurvreg.help
Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data
bayessurvreg1.help
Helping function for Bayesian survival regression models, version 1.
bayesDensity
Summary for the density estimate based on the mixture Bayesian AFT model.
bayesGspline
Summary for the density estimate based on the model with Bayesian G-splines.
sampleCovMat
Compute a sample covariance matrix.
plot.bayesDensity
Plot an object of class bayesDensity
marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate 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.
plot.marginal.bayesGspline
Plot an object of class marginal.bayesGspline
tandmobRoos
Signal Tandmobiel data, version Roos
vecr2matr
Transform single component indeces to double component indeces
print.bayesDensity
Print a summary for the density estimate based on the Bayesian model.
cgd
Chronic Granulomatous Disease data
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.
simult.pvalue
Compute a simultaneous p-value from a sample for a vector valued parameter.
scanFN
Read Data Values
bayessurvreg1.files2init
Read the initial values for the Bayesian survival regression model to the list.
bayessurvreg1
A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components
predictive2
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
tandmob2
Signal Tandmobiel data, version 2
bayessurvreg2.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
bayesHistogram.help
Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
files2coda
Read the sampled values from the Bayesian survival regression model to a coda mcmc object.
rWishart
Sample from the Wishart distribution
give.summary
Brief summary for the chain(s) obtained using the MCMC.
give.init
Check and possibly fill in initial values for the G-spline, augmented observations and allocations for Bayesian models with G-splines
bayessurvreg3.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
rMVNorm
Sample from the multivariate normal distribution
sampled.kendall.tau
Estimate of the Kendall's tau from the bivariate model
traceplot2
Trace plot of MCMC output.
predictive
Compute predictive quantities based on a Bayesian survival regression model fitted using bayessurvreg1 function.
files.Gspline
Write headers to or clean files with sampled G-spline
plot.bayesGspline
Plot an object of class bayesGspline
densplot2
Probability density function estimate from MCMC output
credible.region
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.