Learn R Programming

extremefit (version 1.0.2)

Estimation of Extreme Conditional Quantiles and Probabilities

Description

Extreme value theory, nonparametric kernel estimation, tail conditional probabilities, extreme conditional quantile, adaptive estimation, quantile regression, survival probabilities.

Copy Link

Version

Install

install.packages('extremefit')

Monthly Downloads

331

Version

1.0.2

License

GPL-2

Maintainer

Last Published

May 4th, 2019

Functions in extremefit (1.0.2)

Rectangular.kernel

Rectangular kernel function

Pareto Distribution

Pareto distribution

Epanechnikov kernel function

Computation of the critical value in the hill.adapt function

Pointwise confidence intervals by bootstrap

Pareto mixture distribution

Pointwise confidence intervals by bootstrap

Compute the extreme quantile procedure for Cox model

predict.hill.ts

Predict the adaptive survival or quantile function for a time serie

Predict the adaptive survival or quantile function

plot.hill.adapt

Hill.adapt plot

Triangular kernel function

Goodness of fit test statistics

Probability grid

predict.hill.adapt

Predict the adaptive survival or quantile function

Weighted quantile

goftest.hill.adapt

Goodness of fit test statistics

Biweight.kernel

Biweight kernel function

High-frequency noninvasive valvometry data

Burr Distribution

Burr distribution

Compute the extreme quantile procedure

Compute the extreme quantile procedure on a time dependent data

goftest.hill.ts

Goodness of fit test statistics for time series

Wind speed for Brest (France)

TruncGauss.kernel

Truncated Gaussian kernel function

Choice of the bandwidth by cross validation.

Pareto change point distribution

rburr.dependent

Generate Burr dependent data

predict.cox.adapt

Predict the survival or quantile function from the extreme procedure for the Cox model

Weighted empirical cumulative distribution function

Load curve of an habitation

Gaussian.kernel

Gaussian kernel function