predict.gfcm {cuRe} | R Documentation |
Predict function for flexible mixture cure model
Description
Function for doing predictions for class gfcm
.
Usage
## S3 method for class 'gfcm'
predict(object, newdata = NULL,
type = c("surv", "curerate", "probcure", "survuncured",
"hazarduncured", "cumhazuncured", "densityuncured",
"failuncured", "oddsuncured", "loghazarduncured","hazard",
"density", "fail", "loghazard", "odds", "cumhaz"), indi = TRUE,
time = NULL, var.type = c("ci", "se", "n"), pars = NULL,
link = NULL, keep.attributes = FALSE, ...)
Arguments
object |
Object of class |
newdata |
Data frame from which to compute predictions. If empty, predictions are made on the data which the model was fitted on. |
type |
Prediction type (see details). The default is |
indi |
Logical. If |
time |
Optional time points at which to compute predictions.
This argument is not used if type is |
var.type |
Character. Possible values are " |
pars |
Numerical vector containing the parameters values of the model. In general, this argument can be ignored by the user. |
link |
Character, indicating the link function for the variance calculations.
Possible values are " |
keep.attributes |
Logical. If |
... |
Additional arguments. Currently not used. |
Details
Possible values for argument type
are:
surv
: Survival function
curerate
: The cure fraction
probcure
: The conditional probability of being cured
survuncured
: The survival of the uncured
hazarduncured
: The hazard function of the uncured
cumhazuncured
: The cumulative hazard of the uncured
densityuncured
: The density function of the uncured
failuncured
: The distribution function of the uncured, i.e., 1 - survuncured
oddsuncured
: Odds of the uncured, i.e., (1 - survuncured
) / survuncured
loghazarduncured
: The log-hazard of the uncured
hazard
: The hazard function
density
: The density function
fail
: The distribution function
loghazard
: The log-hazard function
odds
: The odds, i.e., (1 - surv
) / surv
cumhaz
: The cumulative hazard function
Value
A list containing the predictions of each individual in newdata
.