bayesHistogram.help {bayesSurv} | R Documentation

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

### Description

These functions are not to be called by ordinary users.

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

### Usage

    bayesHistogram.design(y1, y2)

    bayesHistogram.checkStore(store)

    bayesHistogram.priorInit(prior, init, mcmc.par, design)

    bayesHistogram.writeHeaders(dir, design, prior.init, store)

### Arguments

`y1` | response for the first dimension. This should be a~survival object created by `Surv`
`y2` | response object for the second dimension (if bivariate density is to be smoothed). This should be a~survival object created by `Surv`. Further, it must be consistent with `y1`, i.e. it has to have the same number of rows.
`store` | a~list with appropriate components
`prior` | a~list as required by `prior` argument of function `bayesHistogram`
`init` | a~list as required by `init` argument of function `bayesHistogram`
`mcmc.par` | a~list as required by `mcmc.par` argument of function `bayesHistogram`
`design` | a~list with the design information as returned by the function `bayesHistogram.design`. The list is assumed to have the following components: y.left ... y.right ... status ... dim ...
`dir` | string giving a~directory where to store sampled files
`prior.init` | an~object as returned by `bayesHistogram.priorInit`

### Value

Some lists.

### Value for bayesHistogram.design

A~list with the following components:

y.left
  vector or matrix with either observed, right or left censored observations or with the lower limits of interval censored observations. It is a vector if `dim == 1` and it is a matrix with 2 rows and n columns if `dim == 2`, where n is a~sample size. In that case, the first row of the matrix are responses for the first dimension and the second row of the matrix are responses for the second dimension.
y.right
  vector or matrix with entries equal to 1 for observed, right or left censored observations and entries equal to the upper limits of interval censored observations. The structure is the same as that of `y.left`.
status
  a~vector or matrix with censoring indicators (1 = exactly observed, 0 = right censored, 2 = left censored, 3 = interval censored). The structure is the same as that of `y.left`.
dim
  dimension of the response, i.e. 1 (univariate smoothing) or 2 (bivariate smoothing)

### Value for bayesHistogram.priorInit

A~list with the following components:

Gparmi
  integer parameters for the G-spline constructor in the C++ code
Gparmd
  double parameters for the G-spline constructor in the C++ code
iter
  index of the nullth iteration
y
  vector of initial values for the response, 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
specification
  specification of the G-spline model (1 or 2), see `bayesHistogram` for more detail

and the following attributes:

init
prior
mcmc.par

### Author(s)

Arnost Komarek arnost.komarek@med.kuleuven.be

[Package bayesSurv version 0.4 Index]