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bayesSurv (version 0.6-2)
Bayesian Survival Regression with Flexible Error and Random Effects Distributions
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Install
install.packages('bayesSurv')
Monthly Downloads
243
Version
0.6-2
License
GPL (>= 2)
Maintainer
Arnošt Komárek
Last Published
January 3rd, 2010
Functions in bayesSurv (0.6-2)
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simult.pvalue
Compute a simultaneous p-value from a sample for a vector valued parameter.
bayessurvreg3.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
bayessurvreg2.help
Helping functions for Bayesian regression with an error distribution smoothed using G-splines
files.Gspline
Write headers to or clean files with sampled G-spline
bayesDensity
Summary for the density estimate based on the mixture Bayesian AFT model.
vecr2matr
Transform single component indeces to double component indeces
scanFN
Read Data Values
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.
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).
files2coda
Read the sampled values from the Bayesian survival regression model to a coda mcmc object.
bayessurvreg1.help
Helping function for Bayesian survival regression models, version 1.
bayesHistogram
Smoothing of a uni- or bivariate histogram using Bayesian G-splines
bayesHistogram.help
Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
bayessurvreg1
A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components
bayesGspline
Summary for the density estimate based on the model with Bayesian G-splines.
tandmob2
Signal Tandmobiel data, version 2
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.
rMVNorm
Sample from the multivariate normal distribution
sampleCovMat
Compute a sample covariance matrix.
print.bayesDensity
Print a summary for the density estimate based on the Bayesian model.
sampled.kendall.tau
Estimate of the Kendall's tau from the bivariate model
densplot2
Probability density function estimate from MCMC output
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
plot.bayesDensity
Plot an object of class bayesDensity
bayessurvreg1.files2init
Read the initial values for the Bayesian survival regression model to the list.
rWishart
Sample from the Wishart distribution
marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate model with Bayesian 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
bayesBisurvreg.help
Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data
traceplot2
Trace plot of MCMC output.
plot.bayesGspline
Plot an object of class bayesGspline
predictive2
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
bayessurvreg.help
Helping function for Bayesian survival regression models.
credible.region
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
tandmobRoos
Signal Tandmobiel data, version Roos
cgd
Chronic Granulomatous Disease data