Abstract: This paper studies a unifying framework for linear Gaussian models used in target tracking. We propose a customized linear Gaussian methodology (Integrated Ornstein-Uhlenbeck in local ...

1 School of Engineering, The University of Tokyo, Tokyo, Japan 2 Interfaculty Initiative in Information Studies, The University of Tokyo, Tokyo, Japan Tracking and manipulating deformable linear ...

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 ...

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 ...

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 ...