Big data analytics (BDA) is one of the most important general-purpose technologies. Despite
the increasing pervasiveness of BDA across industries and some preliminary evidence …

Penalized factor analysis is an efficient technique that produces a factor loading matrix with
many zero elements thanks to the introduction of sparsity-inducing penalties within the …

Excess hazard modelling is one of the main tools in population-based cancer survival
research. Indeed, this setting allows for direct modelling of the survival due to cancer even in …

Regression models describing the joint distribution of multivariate responses conditional on
covariate information have become an important aspect of contemporary regression …

Bivariate survival outcomes arise frequently in applied studies where the occurrence of two
events of interest are associated. Often the exact event times are unknown due to censoring …

Copula‐based survival regression models, which consist of a copula function and marginal
distribution (ie, marginal survival function), have been widely used for analyzing clustered …

Bivariate time-to-event data frequently arise in research areas such as clinical trials and
epidemiological studies, where the occurrence of two events are correlated. In many cases …

This paper presents a novel approach to identifying potential bubbles in the US stock market
by employing alternative time series methods based on long memory, including fractional …

Artificial intelligence (AI) systems have become increasingly common and the trend will
continue. Examples of AI systems include autonomous vehicles (AV), computer vision …

We propose a versatile joint regression framework for count responses. The method is
implemented in the R add-on package GJRM and allows for modelling linear and non-linear …