En este trabajo demostramos que toda distribución hipergeométrica H(N, X,n) puede ser descrita como suma de pruebas independientes con probabilidades de. View distribucion from CFM at Universidad Nacional de Colombia. DISTRIBUCIN HIPERGEOMTRICA. Notacin: Formula: Luego. La distribución hipergeométrica h (x ; m, n, k) se puede aproximar por medio de Esta aplicación muestra gráficamente la aproximación entre distribuciones.
|Published (Last):||23 November 2011|
|PDF File Size:||9.50 Mb|
|ePub File Size:||7.1 Mb|
|Price:||Free* [*Free Regsitration Required]|
In the following theorem, we consider the case where both the random variables are distributed as Gauss hypergeometric. Several univariate and matrix variate generalizations of this distribution are given in Gordy 1. Gokarna Aryal and Saralees Nadarajah. Several gipergeometrica and special cases of this distribution are given in Johnson, Kotz and Balakrishnan 3, p.
This distribution was defined and used by Libby and Novic In this section, we give definitions and results that are used in subsequent sections.
Nagar and Erika Alejandra Rada-Mora. The graph of the Gauss hypergeometric density for different values of the parameters is shown in the Figure 1.
Moreover, the cumulative distribution function CDF can be derived in terms of special functions as shown in the following theorem.
To include the widget in a wiki page, paste the code below into the page source. In this article, we have derived the probability density functions of the product and the quotient of two independent random variables having Gauss hypergeometric distribution. To add the widget to iGoogle, click here. Then, the CDF of X is given by. The following theorem suggests a generalized beta type 2 distribution, from the Gauss hypergeometric distribution.
Finally, applying 10we obtain the desired result. In this article, we derive distributions of the product and the ratio of two independent random variables when at least one of them is Gauss hypergeometric.
In the context of Bayesian analysis of unreported Poisson count data, while deriving the marginal posterior distribution of the reporting distribucon p, Fader and Hardie 8. The generalized beta and F -distributions in statistical modelling. Information matrix for beta distributions.
Advances in distribution theory, order statistics, and inference, ISBN: For details see Nadarajah and Zografos Bayesian inference for linear growth birth and death processes.
Many of the finite range distributions encountered in practice can easily be transformed into the standard beta distribution.
To find the marginal pdf of Zwe integrate 26 with respect to x 2 to get. You will then see the widget on your iGoogle account.
Thus, we obtain the joint pdf of W and Z as. Send feedback Visit Wolfram Alpha. To embed a widget in your blog’s sidebar, install the Wolfram Alpha Widget Sidebar Pluginand copy and paste the Widget ID below into the “id” field:. Make yipergeometrica selections below, then copy distribuciion paste the code below into your HTML source.
A brief introduction of this distribution is given in the encyclopedic work of Johnson, Kotz and Balakrishnan 3, p.
The Appell’s first hypergeometric function F 1 is defined by. These densities have been expressed in terms of Appell’s first hypergeometric function F 1. The above hipregeometrica was suggested by Armero and Bayarri 6.
Distribuciones estadísticas – TheCalculatorStore
In this section, we obtain distributional results for the product of two independent random variables involving Gauss hypergeometric distribution. Services on Demand Article. Using the independence, the joint pdf of X 1 and X 2 is given by.
We appreciate your interest in Wolfram Alpha and will be in touch soon. Now, using the definition of the Appell’s first hypergeometric function, we get the desired result. To add a widget to a MediaWiki site, the wiki must have the Widgets Extension installed, as well as the code for the Distribuvion Alpha distribuclon.
A generalization of the beta distribution distribuciion applications. All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License.
The k -th moment of the variable X having Gauss hypergeometric distribution, obtained in Armero and Bayarri 6.
It is straightforward to show that where 2 F 1 is the Gauss hypergeometric series. To obtain 19we use 7 to write and proceed similarly. Fader and Bruce G.
The joint pdf of X 1 and X 2 is given by