Our research is focused on graph algorithms, from both a theoretical perspective, and a practical perspective motivated by real-world problems in Bioinformatics, such as genome sequencing technologies ...

Maximum likelihood algorithms are described for generalized linear mixed models. I show how to construct a Monte Carlo version of the EM algorithm, propose a Monte Carlo Newton-Raphson algorithm, and ...

A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and ...

In this paper, we propose smoothing algorithms for rating-level PD and rating migration probability. The smoothed estimates obtained by these approaches are optimal in the sense of constrained maximum ...