Extending the traditional discrete choice model by incorporating latent psychological factors can help to better understand the individual's decision-making process and therefore to yield more ...

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 ...

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 ...

This paper develops a method to efficiently estimate hidden Markov models with continuous latent variables using maximum likelihood estimation. To evaluate the (marginal) likelihood function, I ...

Combining inverse-probability weighting based on propensity scores and a semiparametric outcome model with a latent-class variable as an intervening variable, this paper introduces extensions of Rubin ...