A note on finding peakedness in bivariate normal distribution using Mathematica
| Autor: | Masood ul Haq, Ehtisham Hussain, Anwer Khurshid |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2007 |
| Předmět: |
Statistics and Probability
Distribution (number theory) Degree (graph theory) Computation lcsh:Mathematics Mathematical analysis Multivariate normal distribution Management Science and Operations Research Symbolic computation lcsh:QA1-939 Measure (mathematics) Modeling and Simulation Kurtosis Probability distribution Statistics Probability and Uncertainty lcsh:Statistics lcsh:HA1-4737 Mathematics |
| Zdroj: | Pakistan Journal of Statistics and Operation Research, Vol 3, Iss 2, Pp 75-86 (2007) Pakistan Journal of Statistics and Operation Research; Vol 3. No. 2, July 2007; 75-86 |
| ISSN: | 2220-5810 1816-2711 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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