An alternative method for computing mean and covariance matrix of some multivariate distributions

• Autores: R. Radhakrishanan, Askar Choudhury
• Localización: International journal of mathematical education in science and technology, ISSN 0020-739X, Vol. 40, Nº. 3, 2009, págs. 434-440
• Idioma: inglés
• DOI: 10.1080/00207390802419586
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• Resumen

  • Computing the mean and covariance matrix of some multivariate distributions, in particular, multivariate normal distribution and Wishart distribution are considered in this article. It involves a matrix transformation of the normal random vector into a random vector whose components are independent normal random variables, and then integrating univariate integrals for computing the mean and covariance matrix of a multivariate normal distribution. Moment generating function technique is used for computing the mean and covariances between the elements of a Wishart matrix. In this article, an alternative method that uses matrix differentiation and differentiation of the determinant of a matrix is presented. This method does not involve any integration.