predict.hill: Predict the adaptive survival or quantile function

In extremefit: Estimation of Extreme Conditional Quantiles and Probabilities

Predict the adaptive survival or quantile function

Description

Give the adaptive survival function or quantile function

Usage

## S3 method for class 'hill'
predict(
  object,
  newdata = NULL,
  type = "quantile",
  input = NULL,
  threshold.rank = 0,
  threshold = 0,
  ...
)

Arguments

object	output object of the function hill.
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.
threshold.rank	the rank value for the hill output of the threshold, with default value 0.
threshold	the value of threshold, with default value 0.
...	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 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".

See Also

hill

Examples

x <- abs(rcauchy(100))
hh <- hill(x)
#example for a fixed value of threshold
predict(hh, threshold = 3)
#example for a fixed rank value of threshold
predict(hh, threshold.rank = 30)

extremefit documentation built on April 11, 2025, 6:10 p.m.