The analysis of longitudinal dyadic data is challenging due to the complicated correlations within and between dyads, as well as possibly non-ignorable dropouts. Based on a mixed-effects hybrid model, ...

Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model ...

Given the availability of large longitudinal data sets on human height and weight, different modelling approaches are at hand to access quantities of interest relating to important diagnostic aims.

This paper extends the Bayesian Model Averaging framework to panel data models where the lagged dependent variable as well as endogenous variables appear as regressors. We propose a Limited ...

Bayesian Model Averaging (BMA) provides a coherent mechanism to address the problem of model uncertainty. In this paper we extend the BMA framework to panel data models where the lagged dependent ...

We introduce a new framework for counterparty risk model backtesting based on Bayesian methods. This provides a conceptually sound approach for analyzing model performance that is also straightforward ...