عنوان : یک الگوریتم ثانویه برای برازش مدل آمیخته چوله-تی
موضوع : علم داده
سایر نویسندگان : جناب آقای عباس مهدوی (نویسنده مسئول)
کد مقاله : csda1-01060068
ارائه دهنده : عباس مهدوی
متن چکیده : An alternative EM-algorithm to obtain maximum likelihood estimates of the finite mixture of skew-t distributions is introduced. Adopting the new algorithm is simpler respect to exiting algorithms, by reducing the number of conditional expectations in E-step and the number of equations to solve in M-step. The average CPU times shows that this simplification consequence is a considerably reduction of the computational time. Some Monte Carlo simulations are presented to show the maximum likelihood estimates based on the alternative EM-algorithm, provides good asymptotic properties. We illustrate the usefulness of the proposed methodology by analyzing one real data set.