These are just sub-parts of bayesBisurvreg.priorInit and
related functions to make them more readable for the programmer.
give.init.Gspline(prior, init, mcmc.par, dim)give.init.y(init.y, dim, y.left, y.right, status)
give.init.y2(init.y, init2.y, dim, design, design2, doubly)
give.init.r(init.r, init.y, dim, KK,
gamma, sigma, c4delta, intcpt, scale)
prior argument of the function
bayesHistogram or prior and prior2
arguments of the function init argument of the function
bayesHistogram or by init and init2
arguments of the function mcmc.par argument of
function bayesHistogram or by mcmc.par and
mcmc.par2 arguments of the function
bayessurvreg.design related to either the onset time
if doubly censored observations or to the event time. Remark:
design$Y containbayessurvreg.design related to time-to-event
if doubly censored observations. Remark:
design2$Y contains original times and NOT theinit.y.init.y.dim is equal to 1 and
a~matrix with $n$ rows and 2 columns if dim is equal to
2. Values should be ondim with $K$ coefficients
defining the G-spline.dim with initial
$\gamma$ parameters of the G-spline.dim with initial
$\sigma$ parameters of the G-spline.dim with constants to compute the distance between two knots
defining the G-spline.dim with initial values of the
intercept term of the G-spline.dim with initial values of the
scale parameters of the G-spline.init.y, i.e. with 2~columns and
$n$ rows in the case of the bivariate data.