2022, Vol. 3, Issue 2, Part A
Using the nonparametric methods to estimate parameters of The Beta distribution
Author(s): Khalid Talib Othman
Abstract: As a probability function that permits modeling the natural behavior of random variables that may only take values within a specified interval of real numbers with finite length, the Beta distribution has gained significance in the field of applied statistics. Variables with ranges between 0 and 1 (percentages) are a specific instance that arises frequently in practice. The Beta distribution is typically used as a prior distribution when the sample data can be fitted to a binomial distribution; however, in the case of interest for this work, the sample data can be fitted to a Beta distribution, which would entail having a likelihood function that is different from the binomial likelihood function. Therefore, a methodology is proposed in this article to obtain prior distributions for the shape parameters of the Beta distribution. External information on the prior distribution's mean and variance was used to generate a joint distribution for the distribution's parameters. Finally, the marginal distributions of the joint distribution were used to derive the prior distributions for the shape parameters.
Pages: 78-84 | Views: 563 | Downloads: 241
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How to cite this article:
Khalid Talib Othman. Using the nonparametric methods to estimate parameters of The Beta distribution. Journal of Mathematical Problems, Equations and Statistics. 2022; 3(2): 78-84.
