This is a book about statistical distributions, their properties, and their application to
modelling the dependence of the location, scale, and shape of the distribution of a response …

Demands in research investigating small molecules by applying untargeted approaches
have been a key motivator for the development of repositories for mass spectrometry spectra …

This paper introduces a new methodology for the estimation of production functions
satisfying some classical production theory axioms, such as monotonicity and concavity …

Abstract Generalized Linear Models (GLMs) are a popular class of regression models when
the responses follow a distribution in the exponential family. In real data the variability often …

This article studies M-type estimators for fitting robust generalized additive models in the
presence of anomalous data. A new theoretical construct is developed to connect the costly …

This article studies M-type estimators for fitting robust additive models in the presence of
anomalous data. The components in the additive model are allowed to have different …

Recent evidence suggests ever-increasing applications of statistical process control (SPC)
in health data analysis. However, the diversity in numbers and types of included variables …

The validity of estimation and smoothing parameter selection for the wide class of
generalized additive models for location, scale and shape (GAMLSS) relies on the correct …

We are interested in a class of unsupervised methods to detect possible disease outbreaks,
that is, rapid increases in the number of cases of a particular disease that deviate from the …

Estimation of support frontiers and boundaries often involves monotone and/or concave
edge data smoothing. This estimation problem arises in various unrelated contexts, such as …