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.
a numeric vector of data points between 0 and 1.
a number indicating the bandwidth used for the density estimation.
a number determining the correlation coefficient, only used if
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
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
bw are mutually
method = "chen", the kernel function is based on a beta density, according to Chen
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.
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