Description Usage Arguments Details Value Note Examples
View source: R/predict.spdur.R
predict
and related methods for class “spdur
”.
1 2 3 4 5 6 7 8 9 |
object |
Object of class “ |
newdata |
Optional data for which to calculate fitted values, defaults to training data. |
type |
Quantity of interest to calculate. Default conditional hazard,
i.e. conditioned on observed survival up to time |
truncate |
For conditional hazard, truncate values greater than 1. |
na.action |
Function determining what should be done with missing values
in newdata. The default is to predict NA ( |
... |
not used, for compatibility with generic function. |
Calculates various types of probabilities, where “conditional” is used in
reference to conditioning on the observed survival time of a spell up to
time t, in addition to conditioning on any variables included in the
model (which is always done). Valid values for the type
option
include:
“conditional risk”: Pr(Cure=0|Z*gamma, T>t)
“conditional cure”: Pr(Cure=1|Z*gamma, T>t)
“hazard”: Pr(T=t|T>t, C=0, X*beta) * Pr(Cure=0|Z*gamma)
“failure”: Pr(T=t|T>t-1, C=0, X*beta) * Pr(Cure=0|Z*gamma)
“unconditional risk”: Pr(Cure=0|Z*gamma)
“unconditional cure”: Pr(Cure=1|Z*gamma)
“conditional hazard” or “response”: Pr(T=t|T>t, C=0, X*beta) * Pr(Cure=0|Z*gamma, T>t)
“conditional failure”: Pr(T=t|T>t-1, C=0, X*beta) * Pr(Cure=0|Z*gamma, T>t)
The vector Z*gamma indicates the cure/at risk equation covariate vector, while X*beta indicates the duration equation covariate vector.
Returns a data frame with 1 column corresponding to type
, in the same
order as the data frame used to estimate object
.
See forecast.spdur
for producing forecasts when future
covariate values are unknown.
1 2 3 4 5 6 7 | # get model estimates
data(model.coups)
ch <- predict(model.coups)
head(fitted(model.coups))
head(residuals(model.coups))
|
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