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). |
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. |
bayesHistogram |
Smoothing of a uni- or bivariate histogram using Bayesian G-splines |
bayessurvreg1 |
A Bayesian survival regression with an error distribution expressed as a~normal mixture with unknown number of components |
bayessurvreg1.files2init |
Read the initial values for the Bayesian survival regression model to the list. |
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. |
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). |
cgd |
Chronic Granulomatous Disease data |
credible.region |
Compute a simultaneous confidence region from a sample for a vector valued parameter. |
densplot2 |
Probability density function estimate from MCMC output |
files2coda |
Read the sampled values from the Bayesian survival regression model to a coda mcmc object. |
give.summary |
Brief summary for the chain(s) obtained using the MCMC. |
plot.bayesDensity |
Plot an object of class bayesDensity |
plot.bayesGspline |
Plot an object of class bayesGspline |
predictive |
Compute predictive quantities based on a Bayesian survival regression model fitted using bayessurvreg1 function. |
predictive2 |
Compute predictive quantities based on a Bayesian survival regression model fitted using bayesBisurvreg or bayessurvreg2 or bayessurvreg3 functions. |
print.bayesDensity |
Print a summary for the density estimate based on the Bayesian model. |
sampleCovMat |
Compute a sample covariance matrix. |
tandmob2 |
Signal Tandmobiel data, version 2 |
tandmobRoos |
Signal Tandmobiel data, version Roos |
traceplot2 |
Trace plot of MCMC output. |
vecr2matr |
Transform single component indeces to double component indeces |