This book is written for graduate students and researchers, who are interested in using
copula-based models for multivariate data structures. It provides a step-by-step introduction …

Event-based cameras are bioinspired vision sensors whose pixels work independently from
each other and respond asynchronously to brightness changes, with microsecond …

Now in its second edition, this accessible text presents a unified Bayesian treatment of state-
of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state …

Bayesian optimization is a sample-efficient approach to global optimization that relies on
theoretically motivated value heuristics (acquisition functions) to guide its search process …

Bayes factors have been advocated as superior to p-values for assessing statistical
evidence in data. Despite the advantages of Bayes factors and the drawbacks of p-values …

Experiments have long been used to study the relationship between a set of inputs to a
physical system and the resulting output. Termed physical experiments in this text, there is a …

" This is a great overview of the field of model-based clustering and classification by one of
its leading developers. McNicholas provides a resource that I am certain will be used by …

Bayesian Statistics: Page 1 Bayesian Statistics: An Introduction PETER M. LEE Formerly Provost
of Wentworth College, University of York, England Fourth Edition John Wiley & Sons, Ltd Page …

This volume presents in detail the fundamental theories of linear regression analysis and
diagnosis, as well as the relevant statistical computing techniques so that readers are able …

Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R
describes the common underlying theory of multiple comparison procedures through …