| sampled.kendall.tau {bayesSurv} | R Documentation |
This function computes an estimate of the residual (after adjustment
for covariates) Kendall's tau for the bivariate survival model fitted
using the functions bayesHistogram or
bayesBisurvreg.
For both these function their argument prior$specification must
be equal to 2!
When G is a bivariate distribution function, the population version of the Kendall's tau is defined as
tau = 4*int G dG - 1
.
For the model estimated using one of the above mentioned functions the value of Kendall's tau at each iteration of MCMC is equal to
4*sum[i=-K[1]][K[1]]sum[j=-K[2]][K[2]]sum[k=-K[1]][K[1]]sum[l=-K[2]][K[2]] w[i,j]*w[k,l]* Phi((mu[1,i] - mu[1,k])/(sqrt(2)*sigma[1])) * Phi((mu[2,j] - mu[2,l])/(sqrt(2)*sigma[2])) - 1,
where mu[1,-K[1]],...,mu[1,K[1]] are knots in the first margin, mu[2,-K[2]],...,mu[2,K[2]] are knots in the second margin, sigma[1] is the basis standard deviation in the first margin, sigma[2] is the basis standard deviation in the second margin, and w[i,j], i=-K[1],...,K[1], j=-K[2],...,K[2] are the G-spline weights.
sampled.kendall.tau(dir = getwd(), extens = "", K, skip = 0, by = 1, last.iter, nwrite)
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 (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. |
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). |
A vector with sampled values of the Kendall's tau.
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 ## tandmobPA.pdf, tandmobPA.R. ##