The predictive likelihood is useful for ranking models in forecast comparison exercises using Bayesian inference. We discuss how it can be estimated, by means of marginalization, for any subset of the ...

Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a ...

We propose an affine extension of the linear Gaussian term structure model (LGM) such that the instantaneous covariation of the factors is given by an affine process on semidefinite positive matrixes.

Let (Y, (X i ) 1≤i≤p ) be a real zero mean Gaussian vector and V be a subset of {1,...,p}. Suppose we are given n i.i.d. replications of this vector. We propose a new test for testing that Y is ...

Caroline Banton has 6+ years of experience as a writer of business and finance articles. She also writes biographies for Story Terrace. Carl Friedrich Gauss was a child prodigy and a brilliant ...

Methodological Comparison of Mapping the Expanded Prostate Cancer Index Composite to EuroQoL-5D-3L Using Cross-Sectional and Longitudinal Data: Secondary Analysis of NRG/RTOG 0415 The ability to ...

The generation of synthetic market data is widely seen as one of the most promising applications of sophisticated artificial intelligence models, such as generative adversarial networks (GANs) and ...