Markov Chain Monte Carlo (MCMC) methods are now an indispensable tool in scientific
computing. This book discusses recent developments of MCMC methods with an emphasis …

Rotational post hoc transformations have traditionally played a key role in enhancing the
interpretability of factor analysis. Regularization methods also serve to achieve this goal by …

The new social media enabled by the Internet and the Web have deeply changed the ways
in which individuals interact and how knowledge is created and exchanged, which is …

Integration of expression quantitative trait loci (eQTL) into genome-wide association studies
(GWASs) is a promising manner to reveal functional roles of associated single-nucleotide …

If one is to judge by counts of citations of the fundamental paper (Dempster in JRSSB 39: 1–
38, 1977), EM algorithms are a runaway success. But it is surprisingly easy to find published …

Recovery of signals from distorted or noisy observations has been a longstanding research
problem with a wide variety of practical applications. We advocate to approach these types …

This work aim to introduce a new method of estimating the variance components in mixed
linear models. The approach will be done firstly for models with three variance components …

Multivariate probit models have been popularly utilized to analysis multivariate ordinal data.
However, the identifiable multivariate probit models entail the covariance matrix for the …

Regression models often require constraints that can be expressed as non-negativity
constraints. This could be because it makes sense for the underlying modeling context, or it …

The EM algorithm is a widely applicable algorithm for modal estimation but often criticized
for its slow convergence. A new hybrid accelerator named APX-EM is proposed for speeding …