The study shows how probabilistic clustering supports intelligent data transmission strategies. The authors propose leveraging cluster probabilities to define transmission rules: sensors with a high ...

This article discusses the application of the EM algorithm to factor models with dynamic heteroscedasticity in the common factors. It demonstrates that the EM algorithm reduces the computational ...

The stochastic approximation EM (SAEM) algorithm is a simulation-based alternative to the expectation/maximization (EM) algorithm for situations when the E-step is ...

Haplotype inference is an indispensable technique in medical science, especially in genome-wide association studies. Although the conventional method of inference using the expectation-maximization ...

This example estimates the normal SSM of the mink-muskrat data using the EM algorithm. The mink-muskrat series are detrended. Refer to Harvey (1989) for details of this data set. Since this EM ...

Many disease resistance traits in plants have a polygenic background and the disease phenotypes are modified by environmental factors. As a consequence, the phenotypic values usually show a ...