A class of unbiased kernel estimates of a probability density function

Tomasz Rychlik

Applicationes Mathematicae (1995)

  • Volume: 22, Issue: 4, page 485-497
  • ISSN: 1233-7234

Abstract

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We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.

How to cite

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Rychlik, Tomasz. "A class of unbiased kernel estimates of a probability density function." Applicationes Mathematicae 22.4 (1995): 485-497. <http://eudml.org/doc/219109>.

@article{Rychlik1995,
abstract = {We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.},
author = {Rychlik, Tomasz},
journal = {Applicationes Mathematicae},
keywords = {rectangular kernel; kernel function; randomized estimate; probability density function; nonparametric estimate; unbiased estimate; density estimation; unbiasedness; strong consistency; kernel estimates; local behavior},
language = {eng},
number = {4},
pages = {485-497},
title = {A class of unbiased kernel estimates of a probability density function},
url = {http://eudml.org/doc/219109},
volume = {22},
year = {1995},
}

TY - JOUR
AU - Rychlik, Tomasz
TI - A class of unbiased kernel estimates of a probability density function
JO - Applicationes Mathematicae
PY - 1995
VL - 22
IS - 4
SP - 485
EP - 497
AB - We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.
LA - eng
KW - rectangular kernel; kernel function; randomized estimate; probability density function; nonparametric estimate; unbiased estimate; density estimation; unbiasedness; strong consistency; kernel estimates; local behavior
UR - http://eudml.org/doc/219109
ER -

References

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