coefficients is obtained by the Expectation Maximization (EM) method. Furthermore, we present a general formula for the estimation …

first stage a mixture of Student-<I>t</I> densities is fitted to the target using an expectation maximization (EM) algorithm …This paper presents the R-package <B>MitISEM</B> (mixture of <I>t</I> by importance sampling weighted expectation … maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density kernel …

first stage a mixture of Student-<I>t</I> densities is fitted to the target using an expectation maximization (EM) algorithm …This paper presents the R-package <B>MitISEM</B> (mixture of <I>t</I> by importance sampling weighted expectation … maximization) which provides an automatic and flexible two-stage method to approximate a non-elliptical target density kernel …

This paper presents the R-package MitISEM (mixture of t by importance sampling weighted expectation maximization) which … mixture of Student-t densities is fitted to the target using an expectation maximization (EM) algorithm where each step of the …

relationship between the classic MLE method and the combination of the Bayesian updating algorithm and the expectation maximization …