| marginal.bayesGspline {bayesSurv} | R Documentation |
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 G-spline.
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 G-spline evaluated in a grid at each iteration of MCMC.
marginal.bayesGspline(dir = getwd(), extens = "", K, grid1, grid2, skip = 0, by = 1, last.iter, nwrite, only.aver = TRUE)
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
G-splines if more G-splines were used in one simulation (e.g. with
doubly-censored data). According to which
bayes*survreg* function was used, specify the argument
extens in the following way.
|
K |
a~vector of length 2 specifying the number of knots at each side of the middle knot for each dimension of the G-spline. |
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 mixmoment.sim. |
nwrite |
frequency with which is the user informed about the
progress of computation (every nwriteth iteration count of
iterations change). |
only.aver |
TRUE/FALSE, if TRUE only MCMC average is
returned otherwise also values of the marginal G-spline at each iteration are
returned (which might ask for quite lots of memory). |
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 G-spline was computed. |
average |
are McMC averages of the marginal G-spline (vector) evaluated in
grid. |
There exists a method to plot objects of the class marginal.bayesGspline.
Additionally, the object of class marginal.bayesGspline has the following
attributes:
sample.sizesample1only.aver = FALSE.
This a matrix with sample.size columns and length(grid1) rows.
sample2only.aver = FALSE.
This a matrix with sample.size columns and length(grid2) rows.
Arnošt Komárek komarek@karlin.mff.cuni.cz
Komárek, A. (2006). Accelerated Failure Time Models for Multivariate Interval-Censored Data with Flexible Distributional Assumptions. PhD. Thesis, Katholieke Universiteit Leuven, Faculteit Wetenschappen.
Komárek, A. and Lesaffre, E. (2006). Bayesian semi-parametric accelerated failurew time model for paired doubly interval-censored data. Statistical Modelling, 6, 3–22.
## 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 ## as tandmobPA.pdf, tandmobPA.R. ##