A New Weighted Skew Normal Model

  • Forough Naghibi Shahid Chamran University of Ahvaz, Iran
  • Sayed Mohammad Reza Alavi Shahid Chamran University of Ahvaz, Iran
  • Rahim Chinipardaz Shahid Chamran University of Ahvaz, Iran
DOI: https://doi.org/10.19139/soic-2310-5070-1108
Keywords: Skew normal distribution, Absolute-power weight function, simulation, maximum likelihood estimation, geyser data, pollen data, egg size data.

Abstract

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.

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Published
2021-07-12
How to Cite
Naghibi, F., Alavi, S. M. R., & Chinipardaz, R. (2021). A New Weighted Skew Normal Model. Statistics, Optimization & Information Computing, 10(4), 1026-1142. https://doi.org/10.19139/soic-2310-5070-1108
Issue
Vol 10 No 4 (2022)
Section
Research Articles
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