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bayesSurv (version 2.6)

Bayesian Survival Regression with Flexible Error and Random Effects Distributions

Description

Contains Bayesian implementations of Mixed-Effects Accelerated Failure Time (MEAFT) models for censored data. Those can be not only right-censored but also interval-censored, doubly-interval-censored or misclassified interval-censored.

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Version

Install

install.packages('bayesSurv')

Monthly Downloads

839

Version

2.6

License

GPL (>= 2)

Maintainer

Arnošt Komárek

Last Published

July 27th, 2015

Functions in bayesSurv (2.6)

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.
bayesGspline

Summary for the density estimate based on the model with Bayesian G-splines.
bayessurvreg2.help

Helping functions for Bayesian regression with an error distribution smoothed using G-splines
predictive2

Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
bayesHistogram

Smoothing of a uni- or bivariate histogram using Bayesian G-splines
files.Gspline

Write headers to or clean files with sampled G-spline
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).
bayessurvreg1.help

Helping function for Bayesian survival regression models, version 1.
plot.marginal.bayesGspline

Plot an object of class marginal.bayesGspline
marginal.bayesGspline

Summary for the marginal density estimates based on the bivariate model with Bayesian G-splines.
bayesHistogram.help

Helping function for Bayesian smoothing of (bi)-variate densities based on possibly censored data
plot.bayesDensity

Plot an object of class bayesDensity
bayessurvreg3.help

Helping functions for Bayesian regression with an error distribution smoothed using G-splines
give.summary

Brief summary for the chain(s) obtained using the MCMC.
sampleCovMat

Compute a sample covariance matrix.
plot.bayesGspline

Plot an object of class bayesGspline
credible.region

Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
bayessurvreg1

A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components
predictive

Compute predictive quantities based on a Bayesian survival regression model fitted using bayessurvreg1 function.
bayessurvreg3

Cluster-specific accelerated failure time model for multivariate, possibly doubly-interval-censored data with flexibly specified random effects and/or error distribution.
scanFN

Read Data Values
simult.pvalue

Compute a simultaneous p-value from a sample for a vector valued parameter.
give.init

Check and possibly fill in initial values for the G-spline, augmented observations and allocations for Bayesian models with G-splines
tandmob2

Signal Tandmobiel data, version 2
rWishart

Sample from the Wishart distribution
bayessurvreg1.files2init

Read the initial values for the Bayesian survival regression model to the list.
files2coda

Read the sampled values from the Bayesian survival regression model to a coda mcmc object.
rMVNorm

Sample from the multivariate normal distribution
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.
print.bayesDensity

Print a summary for the density estimate based on the Bayesian model.
bayessurvreg.help

Helping function for Bayesian survival regression models.
sampled.kendall.tau

Estimate of the Kendall's tau from the bivariate model
vecr2matr

Transform single component indeces to double component indeces
bayesDensity

Summary for the density estimate based on the mixture Bayesian AFT model.
cgd

Chronic Granulomatous Disease data
densplot2

Probability density function estimate from MCMC output
tandmobRoos

Signal Tandmobiel data, version Roos