In this paper, we propose an expectation-maximization (EM) algorithm based approach for instantaneous frequency (IF) estimation in a Kalman smoother framework. We formulate time-varying AR (TVAR) ...

The EM algorithm framework of for generalized hyperbolic distributions is the basis of our algorithm. Hu, in 2005, provided the unique algorithms for the limiting cases of generalized hyperbolic ...

A missing data analysis is performed using maximum-likelihood estimation, the expectation maximization (EM) algorithm, and the Kalman filter to fill in missing observations and regression parameters, ...

In this paper, we propose a maximum-entropy expectation-maximization (MEEM) algorithm. We use the proposed algorithm for density estimation. The maximum-entropy constraint is imposed for smoothness of ...

This project applies the Expectation-Maximization (EM) algorithm to estimate the relative abundances of RNA isoforms based on RNA-seq read data. The task involved modeling how sequencing reads map to ...

We introduce a maximum Lq-likelihood estimation (MLqE) of mixture models using our proposed expectation-maximization (EM) algorithm, namely the EM algorithm with Lq-likelihood (EM-Lq). Properties of ...

The algorithm for QTL analysis based on the maximization of AUC is also explained. The results of numerical examples serve to illustrate the properties and the validity of our method.