A New Weighted Skew Normal Model
| Autor: | Forough Naghibi, Sayed Mohammad Reza Alavi, Rahim Chinipardaz |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Statistics, Optimization & Information Computing. 10:1026-1142 |
| ISSN: | 2310-5070 2311-004X |
| DOI: | 10.19139/soic-2310-5070-1108 |
| Popis: | Weighted sampling is a useful method for constructing flexible models and analyzing data sets. In this paper, a new weighted distribution of skew normal is introduced with four parameters. The proposed model is a generalized version of several distributions, such as normal, bimodal normal, skew normal and skew bimodal normal-normal. This weighted model is form-invariant under proposed weight function. The basic characteristics of the model are expressed. A method has been used to generate data from the model. The maximum likelihood estimations of parameters are given and evaluated using simulation study. The model is fitted to the three real data sets. The advantage of the proposed model has been shown on the rival distributions using appropriate criteria. |
| Databáze: | OpenAIRE |
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