A note on finding peakedness in bivariate normal distribution using Mathematica

Anwer Khurshid, Ehtisham Hussain, Masood ul Haq

Abstract


Peakedness measures the concentration around the central value. A classical standard measure of peakedness is kurtosis which is the degree of peakedness of a probability distribution. In view of inconsistency of kurtosis in measuring of the peakedness of a distribution, Horn (1983) proposed a measure of peakedness for symmetrically unimodal distributions. The objective of this paper is two-fold. First, Horn’s method has been extended for bivariate normal distribution. Secondly, to show that computer algebra system Mathematica can be extremely useful tool for all sorts of computation related to bivariate normal distribution. Mathematica programs are also provided.

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DOI: http://dx.doi.org/10.18187/pjsor.v3i2.61

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Title

A note on finding peakedness in bivariate normal distribution using Mathematica

Keywords

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Description

Peakedness measures the concentration around the central value. A classical standard measure of peakedness is kurtosis which is the degree of peakedness of a probability distribution. In view of inconsistency of kurtosis in measuring of the peakedness of a distribution, Horn (1983) proposed a measure of peakedness for symmetrically unimodal distributions. The objective of this paper is two-fold. First, Horn’s method has been extended for bivariate normal distribution. Secondly, to show that computer algebra system Mathematica can be extremely useful tool for all sorts of computation related to bivariate normal distribution. Mathematica programs are also provided.

Date

2007-07-01

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol 3. No. 2, July 2007



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810