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Some characteristics of tensor-variate skew-normal distribution and its application in image analysis | ||
Journal of Mahani Mathematical Research | ||
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 18 تیر 1404 اصل مقاله (909.82 K) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22103/jmmr.2025.24813.1763 | ||
نویسندگان | ||
Seyed Ali Asgar Tajadod1؛ Fatemeh Yousefzadeh* 1؛ R.B. Arellano-Valle2؛ Sara Jomhoori1 | ||
1Department of Statistics, University of Birjand, Birjand, Iran | ||
2Department of Estadistica, Pontificia Universidad Catolica de Chile, Santiago, Chile | ||
چکیده | ||
In recent years, due to the increasing growth of technology and new technologies, data is obtained in more complex structures as the main component in analysis. One of these complex structures is tensors. Therefore, in order to answer this need (analysis of data with tensor structure), it is necessary to expand statistical concepts and methods in the field of data with tensor structure. On the other hand, in reality, we may also encounter skew data. Therefore, in this article, we have introduced the skew normal tensor distribution and obtained some of its important statistical properties. Subsequently, we employed the EM algorithm to obtain maximum likelihood estimates of the parameters and assessed their accuracy through simulation studies. Finally, we have shown the effectiveness of the obtained estimators with real data. | ||
کلیدواژهها | ||
Kronecker-separable covariance؛ Multidimensional array؛ Tensor؛ Skew distributions؛ EM algorithm | ||
مراجع | ||
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