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:: Volume 14, Issue 2 (2-2021) ::
J. of Stat. Sci. 2021, 14(2): 449-470 Back to browse issues page
The Convolution of Multivariate Normal and Standard Exponential Distributions: Theory and Application
Mousa Abdi, Mohsen Madadi , Ahad Jamalizadeh
Abstract:   (925 Views)
In this article, a mixture of multivariate normal and standard exponential distributions is investigated. It is shown that the range of skewness and kurtosis coefficients for this distribution is wider than that of the skew-normal distribution. Some properties of this distribution, such as characteristic function, moment generating function, four first moments, skewness and kurtosis of distribution are presented. Also, the distribution of offine transformations and canonical forms of distribution are derived. The maximum likelihood estimation of parameters of the model is computed by using an EM algorithm. To investigate the suitability and efficiency of the model, a simulation study is presented. Finally, two numerical examples with real data sets are studied.
Keywords: Convolution of Multivariate Normal and Standard Exponential Distributions, EM Algorithm, Offine Transformations and Canonical Form.
Full-Text [PDF 302 kb]   (151 Downloads)    
Type of Study: Research | Subject: Statistical Inference
Received: 2019/07/17 | Accepted: 2020/03/10 | Published: 2021/02/28
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Abdi M, Madadi M, Jamalizadeh A. The Convolution of Multivariate Normal and Standard Exponential Distributions: Theory and Application. J. of Stat. Sci.. 2021; 14 (2) :449-470
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Volume 14, Issue 2 (2-2021) Back to browse issues page
مجله علوم آماری – نشریه علمی پژوهشی انجمن آمار ایران Journal of Statistical Sciences
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