leads to biased estimates and adversely affects inference if ignored. In the literature, often convenient distribution … ignored entirely. In this thesis, ways to estimate the parameters of the Ricker model and perform inference while accounting … investigated for data on the abundance and log-abundance scales, and how inference is done via the parametric bootstrap and …

The main goal of this paper is to describe a method for exact inference in general hybrid Bayesian networks (BNs) (with …

In this paper we introduce various set inference problems as they appear in finance and propose practical and powerful … discount factors and the admissible mean-variance sets of asset portfolios. We propose to make inference on such sets using … inference on sets. …

In this paper we consider the problem of inference on a class of sets describing a collection of admissible models as … especially appealing in the target applications. Moreover, the resulting inference procedures are also more powerful than the …

version of the model studied in Bonhomme et al. (2022). We show that inference is possible in this setting using a …