Flexible modeling of how an entire distribution changes with covariates is an important yet
challenging generalization of mean-based regression that has seen growing interest over …

Traditionally, claim counts and amounts are assumed to be independent in non-life
insurance. This paper explores how this often unwarranted assumption can be relaxed in a …

In insurance and related industries including healthcare, it is common to have several
outcome measures that the analyst wishes to understand using explanatory variables. For …

Standard ratemaking techniques in non-life insurance assume independence between the
number and size of claims. Relaxing the independence assumption, this article explores …

In generalized additive models for location, scale and shape (GAMLSS), the response
distribution is not restricted to belong to the exponential family and all the model's …

This article describes the R package gcmr for fitting Gaussian copula marginal regression
models. The Gaussian copula provides a mathematically convenient framework to handle …

Malicious hacking data breaches cause millions of dollars in financial losses each year, and
more companies are seeking cyber insurance coverage. The lack of suitable statistical …

In nonlife insurance, frequency and severity are two essential building blocks in the actuarial
modeling of insurance claims. In this paper, we propose a dependent modeling framework …

The standard GLM and GAM frequency-severity models assume independence between the
claim frequency and severity. To overcome restrictions of linear or additive forms and to …

Generalized additive models for location, scale and shape (GAMLSS) are a popular
extension to mean regression models where each parameter of an arbitrary parametric …