predict.hill.adapt {extremefit} | R Documentation |
Predict the adaptive survival or quantile function
Description
Give the adaptive survival function or quantile function
Usage
## S3 method for class 'hill.adapt'
predict(object, newdata = NULL, type = "quantile",
input = NULL, ...)
Arguments
object |
output object of the function hill.adapt. |
newdata |
optionally, a data frame or a vector with which to predict. If omitted, the original data points are used. |
type |
either "quantile" or "survival". |
input |
optionnaly, the name of the variable to estimate. |
... |
further arguments passed to or from other methods. |
Details
If type = "quantile", newdata
must be between 0 and 1. If type = "survival", newdata
must be in the domain of the data from the hill.adapt
function.
If newdata
is a data frame, the variable from which to predict must be the first one or its name must start with a "p" if type = "quantile" and "x" if type = "survival".
The name of the variable from which to predict can also be written as input
.
Value
The function provide the quantile assiociated to the adaptive model for the probability grid (transformed to -log(1-p) in the output) if type = "quantile". And the survival function assiociated to the adaptive model for the quantile grid if type = "survival".
References
Durrieu, G. and Grama, I. and Jaunatre, K. and Pham, Q.-K. and Tricot, J.-M. (2018). extremefit: A Package for Extreme Quantiles. Journal of Statistical Software, 87, 1–20.
See Also
Examples
x <- rparetoCP(1000)
HH <- hill.adapt(x, weights=rep(1, length(x)), initprop = 0.1,
gridlen = 100 , r1 = 0.25, r2 = 0.05, CritVal=10)
newdata <- probgrid(p1 = 0.01, p2 = 0.999, length = 100)
pred.quantile <- predict(HH, newdata, type = "quantile")
newdata <- seq(0, 50, 0.1)
pred.survival <- predict(HH, newdata, type = "survival")#survival function
#compare the theorical quantile and the adaptive one.
predict(HH, 0.9999, type = "quantile")
qparetoCP(0.9999)
#compare the theorical probability and the adaptive one assiociated to a quantile.
predict(HH, 20, type = "survival")
1 - pparetoCP(20)