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.
Summary for the density estimate based on the model with Bayesian
G-splines.
Helping functions for Bayesian regression with an error distribution
smoothed using G-splines
Compute predictive quantities based on a Bayesian survival regression
model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions.
Smoothing of a uni- or bivariate histogram using Bayesian
G-splines
Write headers to or clean files with sampled G-spline
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).
Helping function for Bayesian survival regression models, version 1.
plot.marginal.bayesGspline
Plot an object of class marginal.bayesGspline
Summary for the marginal density estimates based on the bivariate model with Bayesian
G-splines.
Helping function for Bayesian smoothing of (bi)-variate densities
based on possibly censored data
Plot an object of class bayesDensity
Helping functions for Bayesian regression with an error distribution
smoothed using G-splines
Brief summary for the chain(s) obtained using the MCMC.
Compute a sample covariance matrix.
Plot an object of class bayesGspline
Compute a simultaneous credible region (rectangle) from a sample for a vector valued parameter.
A Bayesian survival regression with an error distribution
expressed as a~normal mixture with unknown number of components
Compute predictive quantities based on a Bayesian survival regression
model fitted using bayessurvreg1 function.
Cluster-specific accelerated failure time model for multivariate,
possibly doubly-interval-censored data with flexibly specified random effects
and/or error distribution.
Read Data Values
Compute a simultaneous p-value from a sample for a vector valued parameter.
Check and possibly fill in initial values for the G-spline, augmented
observations and allocations for Bayesian models with G-splines
Signal Tandmobiel data, version 2
Sample from the Wishart distribution
Read the initial values for the Bayesian survival regression model to the list.
Read the sampled values from the Bayesian survival regression model
to a coda mcmc object.
Sample from the multivariate normal distribution
Helping function for Bayesian regression with smoothed bivariate
densities as the error term,
based on possibly censored data
Trace plot of MCMC output.
Print a summary for the density estimate based on the Bayesian model.
Helping function for Bayesian survival regression models.
Estimate of the Kendall's tau from the bivariate model
Transform single component indeces to double component indeces
Summary for the density estimate based on the mixture Bayesian AFT model.
Chronic Granulomatous Disease data
Probability density function estimate from MCMC output
Signal Tandmobiel data, version Roos