In this talk, I will discuss the development of interpretable machine learning models to test scientific hypotheses, with a specific focus on spinal motor control. Voluntary movement requires ...

In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...

Dynamical systems modeling is one of the most successfully implemented methodologies throughout mathematical oncology (1). Applications of these model first approaches have led to important insights ...

This article argues that, to relieve the specification difficulties that frequently accompany latent variable models, a first application should in most cases employ an estimator that makes no ...

We analyze the mathematical structure of portfolio credit risk models with particular regard to the modelling of dependence between default events in these models. We explore the role of copulas in ...

In this paper, we propose a latent variable credit risk model for large loan port- folios. It employs the concept of nested Archimedean copulas to account for both a sector-type dependence structure ...

This is a preview. Log in through your library . Abstract We consider the estimation of the number of severely disabled people by using data from the Italian survey on 'Health conditions and appeal to ...

This webpage provides information about the research project “Methods for the Analysis of Longitudinal Dyadic Data, with Applications to Intergenerational Exchanges of Family Support”. The three-year ...