Meta-analysis in the presence of unexplained heterogeneity is frequently undertaken by
using a random-effects model, in which the effects underlying different studies are assumed …

Introduction and hypothesis Diabetes affects bone metabolism. The hypothesis was that type
1 (T1D) and type 2 (T2D) affects BMD and fracture risk differently. Material and methods …

This book is about learning from data using the Generalized Additive Models for Location,
Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and …

The only single-source——now completely updated and revised——to offer a unified
treatment of the theory, methodology, and applications of the EM algorithm Complete with …

The viewpoint taken in much of this text is that PCA is mainly a descriptive tool with no need
for rigorous distributional or model assumptions. This implies that it can be used on a wide …

Hidden Markov models—most often abbreviated to the acronym “HMMs”—are one of the
most successful statistical modelling ideas that have came up in the last forty years: the use …

This Set Contains: Continuous Multivariate Distributions, Volume 1, Models and
Applications, 2nd Edition by Samuel Kotz, N. Balakrishnan and Normal L. Johnson …

This paperback edition, a reprint of the 2001 edition, is a graduate-level textbook that
introduces Bayesian statistics and decision theory. It covers both the basic ideas of statistical …

This book unifies and extends latent variable models, including multilevel or generalized
linear mixed models, longitudinal or panel models, item response or factor models, latent …

Modelling based on finite mixture distributions is a rapidly developing area with the range of
applications exploding. Finite mixture models are nowadays applied in such diverse areas …