give.init {bayesSurv} | R Documentation |
These functions are not to be called by ordinary users.
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 |
a~list as required by prior argument of the function
bayesHistogram or prior and prior2
arguments of the function bayesBisurvreg
|
init |
a~list as required by init argument of the function
bayesHistogram or by init and init2
arguments of the function bayesBisurvreg
|
mcmc.par |
a~list as required by mcmc.par argument of
function bayesHistogram or by mcmc.par and
mcmc.par2 arguments of the function
bayesBisurvreg
|
dim |
dimension of the G-spline/response, 1 or 2. |
init.y |
initial (augmented) observations possibly given by the user. They are partially checked for consistency and these supplied by the user used in the resulting object. This should be either vector of length n where n is a~sample size if the dimension is one or a~matrix with 2 columns and n rows if the dimension is two. |
init2.y |
initial (augmented) times-to-event (if doubly censoring) possibly given by the user. They are partially checked for consistency and these supplied by the user used in the resulting object. This should be either vector of length n where n is a~sample size if the dimension is one or a~matrix with 2 columns and n rows if the dimension is two. |
design |
an~object as returned by the function
bayessurvreg.design related to either the onset time
if doubly censored observations or to the event time. Remark:
design$Y contains original times and NOT their logarithmic
transformations.
|
design2 |
an~object as returned by the function
bayessurvreg.design related to time-to-event
if doubly censored observations. Remark:
design2$Y contains original times and NOT their logarithmic
transformations.
|
doubly |
logical indicating whether the response is doubly censored or not |
y.left |
observed, left or right censored log(event time) or the lower limit
of the interval censored observation. Sorted in a~transposed order compared
to init.y .
|
y.right |
upper limit of the interval censored observation, whatever if the observation
is not interval-censored sorted in a~transposed order compared to init.y .
|
status |
status indicator vector/matrix. 1 for observed times, 0 for right censored times, 2 for left censored times, 3 for interval censored times. |
init.r |
initial allocations possibly given by the user. This should be a~vector of length
n where n is a~sample size if dim is equal to 1 and
a~matrix with n rows and 2 columns if dim is equal to
2. Values should be on the scale
-K[j],...,K[j],
j=1,...,dim
|
init.y |
correctly computed initial observations the G-spline is estimated from. In the case of regression
these should be replaced by residuals. This must be either a~vector or matrix (in the format as returned
by the function give.init.y ).
|
KK |
vector of length dim with K coefficients
defining the G-spline.
|
gamma |
vector of length dim with initial
gamma parameters of the G-spline.
|
sigma |
vector of length dim with initial
sigma parameters of the G-spline.
|
c4delta |
vector of length dim with constants to compute the distance between two knots
defining the G-spline.
|
intcpt |
vector of length dim with initial values of the
intercept term of the G-spline.
|
scale |
vector of length dim with initial values of the
scale parameters of the G-spline.
|
Some lists.
A~list with the following components:
bayesHistogram
for more detailand the following attributes:
init |
prior |
mcmc.par |
A~vector or matrix with the same structure as init.y
, i.e. with 2~columns and
n rows in the case of the bivariate data.
A~list with the following components:
bayesBisurvreg
, related to the onset time in the case of
doubly censoring and to the event time otherwisebayesBisurvreg
, related to the onset time in the case of
doubly censoring and to the event time otherwisebayesBisurvreg
related to the onset time in the case of
doubly censoring and to the event time otherwisebayesBisurvreg
, related to time-to-event in the
case of doubly censoring, equal to 0 if there is no doubly-censoringbayesBisurvreg
, related to time-to-event in the
case of doubly censoring, equal to 0 if there is no doubly-censoringTo be added somewhen...
Arnošt Komárek arnost.komarek[AT]mff.cuni.cz