A growing interest in non-Gaussian time series, particularly in series comprised of
nonnegative integers (counts), is taking place in today's statistics literature. Count series …

The purpose of this article is to provide a survey of the various stages in the development of
response surface methodology (RSM). The coverage of these stages is organized in three …

We present a brief history of the field of interpretable machine learning (IML), give an
overview of state-of-the-art interpretation methods and discuss challenges. Research in IML …

A much-needed introduction to the field of discrete-valued time series, with a focus on count-
data time series Time series analysis is an essential tool in a wide array of fields, including …

A valuable overview of the most important ideas and results in statistical modeling Written by
a highly-experienced author, Foundations of Linear and Generalized Linear Models is a …

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 …

In this article, we introduce the BART R package which is an acronym for Bayesian additive
regression trees. BART is a Bayesian nonparametric, machine learning, ensemble …

Supplement to “Penalising Model Component Complexity: A Principled, Practical Approach
to Constructing Priors”. The supplementary material contains the proofs of all theorems …

Researchers in comparative research increasingly use multilevel models to test effects of
country‐level factors on individual behavior and preferences. However, the asymptotic …

A critical property of count data is its mean–variance relationship, yet this is rarely
considered in multivariate analysis in ecology. 2. This study considers what is being …