There has been a renewed interest in developing more flexible statistical distributions in
recent decades. A major milestone in the methods for generating statistical distributions is …

This chapter describes reference analysis, a method to produce Bayesian inferential
statements which only depend on the assumed model and the available data. Statistical …

With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling
of cryptocurrencies. This paper provides the first GARCH modelling of the seven most …

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 …

Abstract Did Corporate Social Responsibility investing benefit shareholders during the
COVID-19 pandemic crisis? Distinguishing between downside tail risk and upside reward …

We test the presence of regime changes in the GARCH volatility dynamics of Bitcoin log–
returns using Markov–switching GARCH (MSGARCH) models. We also compare …

Interest in the skew-normal and related families of distributions has grown enormously over
recent years, as theory has advanced, challenges of data have grown, and computational …

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 …

A general class of statistical models for a univariate response variable is presented which
we call the generalized additive model for location, scale and shape (GAMLSS). The model …

A new edition of the trusted guide on commonly used statistical distributions Fully updated to
reflect the latest developments on the topic, Statistical Distributions, Fourth Edition continues …