| dc.contributor.author | Okuto, Erick | |
| dc.date.accessioned | 2021-04-08T06:22:28Z | |
| dc.date.available | 2021-04-08T06:22:28Z | |
| dc.date.issued | 6/10/2018 | |
| dc.identifier.issn | 2456-1452 | |
| dc.identifier.uri | http://ir.jooust.ac.ke:8080/xmlui/handle/123456789/9382 | |
| dc.description.abstract | A probability distribution can be constructed by mixing two distributions. Binomial distribution when compounded with beta distribution as prior forms a binomial mixture that is a continuous distribution. Skellam 1948, mixed a binomial distribution with its parameter being the probability of success considered as a random variable taking beta distribution. Probability distributions with binomial outcome tend to fail to fit empirical data due to over-dispersion. To address this challenge binomial mixtures are modeled to cater for the influence caused by over-dispersion. This paper focuses on binomial mixture with a four parameter generalized beta mixing distributions. In particular it focuses on application of McDonald generalized and Gerstenkon generalized mixing distributions. The binomial mixture obtained is proved to be a probability density function. Its moments are obtained using probability generating function techniques. The binomial mixture obtained can be applicable to probability distributions whose outcome are binomial in nature. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | International Journal of Statistics and Applied Mathematics | en_US |
| dc.subject | Probability distribution | en_US |
| dc.subject | Binomial mixture | en_US |
| dc.subject | Four parameter generalized beta distribution | en_US |
| dc.subject | Over-dispersion | en_US |
| dc.subject | Moments | en_US |
| dc.title | Binomial Mixture Based on Generalized Four Parameter Beta Distribution as Prior | en_US |
| dc.type | Article | en_US |
