| contributor author | U.J. Dixit | en |
| contributor author | مهدی جباری نوقابی | en |
| contributor author | Mehdi Jabbari Nooghabi | fa |
| date accessioned | 2020-06-06T13:10:03Z | |
| date available | 2020-06-06T13:10:03Z | |
| date issued | 2011 | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/3344283?show=full | |
| description abstract | The maximum likelihood (ML) and uniformly minimum variance unbiased estimators (UMVUE) of the probability density function (pdf), cumulative distribution function (cdf) and rth moment are derived for the Paretodistribution in the presence of outliers. It has been shown that MLE of pdf and cdf are better than their UMVUEs. At the end, these methods are illustrated with the help of real data from an insurance company. | en |
| language | English | |
| title | Efficient estimation in the Pareto distribution with the presence of outliers | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | Paretodistribution | en |
| subject keywords | Maximum likelihood estimator | en |
| subject keywords | Uniformly minimum variance unbiased estimator | en |
| subject keywords | Probability density function | en |
| subject keywords | Cumulative distribution function | en |
| subject keywords | rth moment | en |
| subject keywords | Outliers | en |
| subject keywords | Insurance | en |
| journal title | Statistical Methodology | fa |
| pages | 340-355 | |
| journal volume | 8 | |
| journal issue | 4 | |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1030789.html | |
| identifier articleid | 1030789 | |
