Methods of the generic function print
, fitted
and predict
for objects inheriting from class cSFM.
"print"(x, ...)
"fitted"(object, quantile = TRUE, quantile.level = c(0.5, 0.8, 0.9, 0.95, 0.99), ...)
"predict"(object, newdata, cp.valid, tp.valid = NULL, ...)
cSFM.est
cSFM.est
quantile = TRUE
newdata
with length nrow{newdata}
newdata
with length ncol{newdata}
; See "Details".predict
, each row of newdata
corresponds to covariate information cp.valid
,
while the column is for the time points tp.valid
. When tp.valid
is null
, then we assume the validation
data set has the same time points as the training data set, which is used to obtain object
.
cSFM.est
, print
, fitted
, predict