bayesBisurvreg.help {bayesSurv} | R Documentation

## Helping function for Bayesian regression with smoothed bivariate densities as the error term, based on possibly censored data

### Description

These functions are not to be called by ordinary users.

These are just sub-parts of `bayesBisurvreg' function to make it more readable for the programmer.

### Usage

    bayesBisurvreg.checkStore(store)

    bayesBisurvreg.priorInit(dim, prior, init, design, mcmc.par,
                                  prior2, init2, design2, mcmc.par2,
                             doubly)

    bayesBisurvreg.priorBeta(prior.beta, init, design)

    bayesBisurvreg.writeHeaders(dir, dim, nP, doubly, prior.init, store,
                                design, design2)

### Arguments

`store` | a~list as required by the argument `store` of the function `bayesBisurvreg`
`dim` | dimension of the response, 1 or 2
`prior` | a~list as required by the argument `prior` of the function `bayesBisurvreg`
`prior2` | a~list as required by the argument `prior2` of the function `bayesBisurvreg`
`init` | a~list as required by the argument `init` of the function `bayesBisurvreg`
`init2` | a~list as required by the argument `init2` of the function `bayesBisurvreg`
`mcmc.par` | a~list as required by the argument `mcmc.par` of the function `bayesBisurvreg`
`mcmc.par2` | a~list as required by the argument `mcmc.par2` of the function `bayesBisurvreg`
`design` | an~object as returned by the function `bayessurvreg.design` related to either the onset time if doubly censored observations or to the event time. Remark: `design$Y` contains original times and NOT their logarithmic transformations.
`design2` | an~object as returned by the function `bayessurvreg.design` related to time-to-event if doubly censored observations. Remark: `design2$Y` contains original times and NOT their logarithmic transformations.
`doubly` | logical indicating whether the response is doubly censored or not
`prior.beta` | a~list as required by the argument `prior.beta` or `prior.beta2` of the function `bayesBisurvreg`
`dir` | path to the directory where the sampled values are to be stored
`nP` | sample size - number of observations if the univariate model is fitted, number of bivariate observational vectors if the bivariate model is fitted
`prior.init` | a~list as returned by the function `bayesBisurvreg.priorInit`
`store` | a~list as returned by the function `bayesBisurvreg.checkStore`

### Value

Some lists.

### Value for bayesBisurvreg.priorInit

A~list with the following components:

Gparmi
  integer arguments for the G-spline constructor in the C++ code related to the onset/event time
Gparmd
  double arguments for the G-spline constructor in the C++ code related to the onset/event time
y
  vector of initial values for the log(onset time)/log(event time), sorted as y[1,1],y[1,2], ..., y[n,1],y[n,2] in the case of bivariate response with sample size equal to n
r
  initial component labels (vector of size n) taking values from 1 to the total length of the G-spline related to the onset/event time
Gparmi2
  integer arguments for the G-spline constructor in the C++ code related to time-to-event in the case of doubly censoring
Gparmd2
  double arguments for the G-spline constructor in the C++ code related to time-to-event in the case of doubly censoring
y2
  vector of initial values for the time-to-event in the case of doubly censoring sorted as

  y[1,1],y[1,2], ..., y[n,1],y[n,2]

  in the case of bivariate response with sample size equal to n

r2
  initial component labels (vector of size n) taking values from 1 to the total length of the G-spline related to time-to-event in the case of doubly censoring
iter
  index of the nullth iteration
specification
  2 component vector (one component for onset, one for time-to-event), specification of the G-spline model (1 or 2), see `bayesHistogram` for more detail
y.left
  lower limit of the log-response (or exact/right/left censored observation) as required by the C++ function `bayesBisurvreg`, related to the onset time in the case of doubly censoring and to the event time otherwise
y.right
  upper limit of the log-response as required by the C++ function `bayesBisurvreg`, related to the onset time in the case of doubly censoring and to the event time otherwise
status
  status vector as required by the C++ function `bayesBisurvreg` related to the onset time in the case of doubly censoring and to the event time otherwise
t2.left
  lower limit of the response as required by the C++ function `bayesBisurvreg`, related to time-to-event in the case of doubly censoring, equal to 0 if there is no doubly-censoring
t2.right
  upper limit of the response as required by the C++ function `bayesBisurvreg`, related to time-to-event in the case of doubly censoring, equal to 0 if there is no doubly-censoring
status2
  status vector related to time-to-event in the case of doubly censoring, equal to 0 otherwise.

and the following attributes:

init
prior
mcmc.par
init2
prior2
mcmc.par2

### Value for bayesBisurvreg.priorBeta

A~list with the following components:

parmI
  integer arguments for C++ `classBetaGamma` constructor
parmD
  double arguments for C++ `classBetaGamma` constructor

and the following attributes:

init
  a~vector with initial values of the beta parameter, equal to `numeric(0)` if there are no regressors
prior.beta
  a~list with components `mean.prior` and `var.prior` containing vectors with the prior mean and prior variance of the `beta` parameters

### Author(s)

Arnost Komarek arnost.komarek@med.kuleuven.be

[Package bayesSurv version 0.4 Index]