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2019•International journal of statistics and applicationsOpen access

A Study of the Ability of the Kernel Estimator of the Density Function for Triangular and Epanechnikov Kernel or Parabolic Kernel

Didier Alain Njamen Njomen, Ludovic Kakmeni Siewe

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Abstract

In this paper, we are interested in the nonparametric estimation of probability density. From the « Rule of thumb » method, we were able to determine the smoothing parameter of the Parsen-Rosenblatt kernel estimator for the density function. Our study is illustrated by numerical simulations to show the performance of the triangular core and Epanechnikov or parabolic density estimator studied.

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What this paper is about

In this paper, we are interested in the nonparametric estimation of probability density. From the « Rule of thumb » method, we were able to determine the smoothing parameter of the Parsen-Rosenblatt kernel estimator for the density function. Our study is illustrated by numerical simulations to show the performance of the triangular core and Epanechnikov or parabolic density estimator studied.

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Available abstract

In this paper, we are interested in the nonparametric estimation of probability density. From the « Rule of thumb » method, we were able to determine the smoothing parameter of the Parsen-Rosenblatt kernel estimator for the density function. Our study is illustrated by numerical simulations to show the performance of the triangular core and Epanechnikov or parabolic density estimator studied.

Key concepts: Variable kernel density estimation, Kernel density estimation, Multivariate kernel density estimation, Mathematics, Kernel smoother, Kernel (algebra), Estimator, Smoothing

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A Study of the Ability of the Kernel Estimator of the Density Function for Triangular and Epanechnikov Kernel or Parabolic Kernel — Research Paper | ScholarLens