marginal.bayesGspline {bayesSurv}  R Documentation 
Summary for the marginal density estimates based on the bivariate model with Bayesian Gsplines.
Description
Compute the estimate of the marginal density function based on the values sampled using the MCMC (MCMC average evaluated in a grid of values) in a model where density is specified as a bivariate Bayesian Gspline.
This function serves to summarize the MCMC chains related to the distributional parts
of the considered models obtained using the functions:
bayesHistogram
and bayesBisurvreg
.
If asked, this function returns also the values of the marginal Gspline evaluated in a grid at each iteration of MCMC.
Usage
marginal.bayesGspline(dir, extens = "", K, grid1, grid2,
skip = 0, by = 1, last.iter, nwrite, only.aver = TRUE)
Arguments
dir 
directory where to search for files (‘mixmoment.sim’, ‘mweight.sim’, ‘mmean.sim’, ‘gspline.sim’) with the MCMC sample. 
extens 
an extension used to distinguish different sampled
Gsplines if more Gsplines were used in one simulation (e.g. with
doublycensored data). According to which

K 
a~vector of length 2 specifying the number of knots at each side of the middle knot for each dimension of the Gspline. 
grid1 
grid of values from the first dimension at which the sampled marginal densities are to be evaluated. 
grid2 
grid of values from the second dimension at which the sampled marginal densities are to be evaluated. 
skip 
number of rows that should be skipped at the beginning of each *.sim file with the stored sample. 
by 
additional thinning of the sample. 
last.iter 
index of the last row from *.sim files that should be
used. If not specified than it is set to the maximum available
determined according to the file 
nwrite 
frequency with which is the user informed about the
progress of computation (every 
only.aver 

Value
An object of class marginal.bayesGspline
is returned. This object is a
list with components margin1
and margin2
(for two margins).
Both margin1
and margin2
components are data.frames with
columns named grid
and average
where
grid 
is a grid of values (vector) at which the McMC average of the marginal Gspline was computed. 
average 
are McMC averages of the marginal Gspline (vector) evaluated in

There exists a method to plot objects of the class marginal.bayesGspline
.
Attributes
Additionally, the object of class marginal.bayesGspline
has the following
attributes:
sample.size
a length of the McMC sample used to compute the McMC average.
sample1
marginal (margin = 1) Gspline evaluated in a grid of values. This attribute is present only if
only.aver = FALSE
.This a matrix with
sample.size
columns and length(grid1) rows.sample2
marginal (margin = 2) Gspline evaluated in a grid of values. This attribute is present only if
only.aver = FALSE
.This a matrix with
sample.size
columns and length(grid2) rows.
Author(s)
Arnošt Komárek arnost.komarek@mff.cuni.cz
References
Komárek, A. (2006). Accelerated Failure Time Models for Multivariate IntervalCensored Data with Flexible Distributional Assumptions. PhD. Thesis, Katholieke Universiteit Leuven, Faculteit Wetenschappen.
Komárek, A. and Lesaffre, E. (2006). Bayesian semiparametric accelerated failurew time model for paired doubly intervalcensored data. Statistical Modelling, 6, 3  22.
Examples
## See the description of R commands for
## the models described in
## Komarek (2006),
## Komarek and Lesaffre (2006),
##
## R commands available
## in the documentation
## directory of this package
##  see extandmobPA.R and
## https://www2.karlin.mff.cuni.cz/~komarek/software/bayesSurv/extandmobPA.pdf
##