knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)

kader

The goal of kader is to supply functions to compute nonparametric kernel estimators for

The functions are based on the theory introduced in

A very brief summary of the theory and sort of a vignette is presented in Eichner, G. (2017): Kader - An R package for nonparametric kernel adjusted density estimation and regression. In: Ferger, D., et al. (eds.): From Statistics to Mathematical Finance, Festschrift in Honour of Winfried Stute. Springer International Publishing. To appear in Jan. 2018. DOI then(!) presumably: 10.1007/978-3-319-50986-0.

Installation

You can install kader from CRAN with:

install.packages("kader")

or from github with:

# install.packages("devtools")
devtools::install_github("GerritEichner/kader")

Example

This example shows you how to estimate at $x_0 = 2$ the value of the density function of the probability distribution underlying Old-Faithful's eruptions data using the (nonrobust) method of Srihera & Stute (2011). The initial grid (given to Sigma) on which the minimization of the estimated MSE as a function of a (kernel-adjusting) scale parameter $\sigma$ is started is rather coarse here to save computing time.

library(kader)
x0 <- 2
sigma <- seq(0.01, 10, length = 21)
fit <- kade(x = x0, data = faithful$eruptions, method = "nonrobust",
  Sigma = sigma, ticker = TRUE)
print(fit)


GerritEichner/kader documentation built on May 10, 2019, 1:14 p.m.