Description Usage Arguments Details Value References See Also Examples

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.

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`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.

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