In this paper, we consider two kinds of special matrices, which are called Ppoeplitz matrix and Ppankel matrix. The idea of matrix transformation is used to compute the determinants and inverses of the Ppoeplitz matrix and the Ppankel matrix. We develop efficient formulas for inverting the Ppoeplitz matrix and the Ppankel matrix. Specifically, for inverting the Ppoeplitz matrix and the Ppankel matrix using our proposed formulas, which only 11 entries need to be calculated when n is even, only 12 entries need to be calculated when n is odd. An example is given to illustrate the formulas.
Inspired by the work of Adcock, Landsman, and Shushi (2019) which established the Stein’s lemma for generalized skew-elliptical random vectors, we derive Stein type lemmas for location-scale mixture of generalized skew-elliptical random vectors. Some special cases such as the location-scale mixture of elliptical random vectors, the location-scale mixture of generalized skew-normal random vectors, and the location-scale mixture of normal random vectors are also considered. As an application in risk theory, we give a result for optimal portfolio selection.
This paper deals with the multivariate tail conditional expectation (MTCE) for generalized skew-elliptical distributions. We present tail conditional expectation for univariate generalized skew-elliptical distributions and MTCE for generalized skew-elliptical distributions. There are many special cases for generalized skew-elliptical distributions, such as generalized skew-normal, generalized skew Student-t, generalized skew-logistic and generalized skew-Laplace distributions.
In this paper, the multivariate tail covariance (MTCov) for generalized skewelliptical distributions is considered. Some special cases for this distribution, such as generalized skew-normal, generalized skew student-t, generalized skew-logistic and generalized skew-Laplace distributions, are also considered. In order to test the theoretical feasibility of our results, the MTCov for skewed and non skewed normal distributions are computed and compared. Finally, we give a special formula of the MTCov for generalized skew-elliptical distributions.
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