Van Niekerk, JanetBekker, Andriette, 1958-Arashi, MohammadDe Waal, Duan J.31cca2cb-0f0b-4ea7-a9c1-9711569804a72016-07-272016-07-272016Van Niekerk, J, Bekker, A & Arashi, M 2016, 'Estimation under the matrix variate elliptical model', South African Statistical Journal, vol. 50, no. 1, pp. 189-171.0038-271Xhttp://hdl.handle.net/2263/56047The problem of estimation within the matrix variate elliptical model is addressed. In this paper a subjective Bayesian approach is followed to derive new estimators for the parameters of the matrix variate elliptical model by assuming the previously intractable normal-Wishart prior. These new estimators are compared to the estimators derived under a normal-inverse Wishart prior as well as the objective Jeffreys’ prior which results in the maximum likelihood estimators, using different measures. A valuable contribution is the development of algorithms for the simulation of the posterior distributions of the matrix variate parameters with emphasis on the new proposed estimators. A simulation study as well as Fisher’s Iris data set are used to illustrate the novelty of these new estimators and to investigate the accuracy gained by assuming the normal-Wishart prior.enSouth African Statistical AssociationBayesian inferenceBessel function of matrix argumentCharacteristic matrixMatrix variate elliptical modelMaximum posterior modeNormal-inverse WishartNormal-WishartSquared error lossArticle