kernel_density_estimator: Construct a Kernel Density Estimator

In hericks/KDE: Kernel Density Estimation

Description

The kernel_density_estimator function builds a kernel density estimator using the provided kernel, bandwidth and samples.

Usage

kernel_density_estimator(kernel, samples, bandwidth = 1, subdivisions = 1000L)

Arguments

kernel	a kernel as S3 object of the class Kernel.
samples	numeric vector; the observations.
bandwidth	non-negative numeric scalar; the bandwidth for the estimator.
subdivisions	positive numeric scalar; subdivisions parameter internally passed to integrate_primitive.

Details

The validation of the returned estimator as IntegrableFunction relies on the function integrate_primitive, thus the subdivisions parameter.

Value

The estimator as S3 object of class IntegrableFunction.

Source

Nonparametric Estimation, Comte [2017], ISBN: 978-2-36693-030-6

See Also

Kernel for more information about kernels, pco_method, cross_validation and goldenshluger_lepski for automatic bandwidth-selection algorithms.

hericks/KDE documentation built on Aug. 22, 2020, 12:04 a.m.