| نویسندگان | Fatemeh Yousefzadeh,seyed ali asghar tajadod,Raynaldo Boris Arellano-Valle |
| نشریه | Mathematics Interdisciplinary Research |
| شماره صفحات | 299-319 |
| شماره سریال | 11 |
| شماره مجلد | 3 |
| نوع مقاله | Full Paper |
| تاریخ انتشار | 2026 |
| نوع نشریه | چاپی |
| کشور محل چاپ | ایران |
| کلید واژه ها | Kronecker, separable covariance, Multidimensional array, Tensor, EM algorithm, Image learning. |
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چکیده مقاله
In recent years, rapid technological advances have led to the emergence of
increasingly complex data structures, among which tensor data play a central
role. To address the challenges of analyzing such data, it is essential to
extend statistical concepts and methodologies to the tensor domain. In this
paper, we introduce the tensor-variate t and skew-t distributions and derive
several of their statistical properties. Parameter estimation is carried out
using the Expectation–Maximization (EM) algorithm, and the performance
of the proposed estimators is assessed through extensive simulation studies.
Finally, the effectiveness and practical applicability of the estimators are
demonstrated using real world data.
لینک ثابت مقاله