pvaldens {bootruin} | R Documentation |
This function computes density estimators for densities with the unit interval as support. One example of data with such a density are p-values. Currently, two methods are implemented that differ in the kernel function used for estimation.
pvaldens(x, bw, rho, method = c("jh", "chen"))
x |
a numeric vector of data points between 0 and 1. |
bw |
a number indicating the bandwidth used for the density estimation. |
rho |
a number determining the correlation coefficient, only used if |
method |
a character string determining the kernel function that is used, see Details. |
Depending on which method
is selected, a different kernel function is used for the
estimation. Since the support of the estimated function is bounded, those kernel functions are
location-dependent.
If method = "jh"
, a Gaussian copula-based kernel function according to Jones and Henderson
(2007) is used. In this case the bandwidth can either be specified directly or as correlation
coefficient: if rho > 0 denotes the correlation coefficient and h > 0 the
bandwidth, then h^2 = 1 - rho. Note that rho
and bw
are mutually
exclusive.
For method = "chen"
, the kernel function is based on a beta density, according to Chen
(1999).
See the cited articles for more details.
A function with a single vector-valued argument that returns the estimated density at any given point(s).
Jones, M. C. and Henderson, D. A. (2007) Kernel-Type Density Estimation on the Unit Interval. Biometrika, 94(4), pp. 977–984.
Chen, S. X. (1999) A Beta Kernel Estimation for Density Functions. Computational Statistics and Data Analysis, 31(2), pp. 131–145.
require(graphics) x <- rbeta(100, 2, 5) fhat <- pvaldens(x, rho = 0.9, method = "jh") hist(x, freq = FALSE, xlim = c(0, 1)) curve(fhat(x), from = 0, to = 1, add = TRUE, col = 2) box()