Related papers: Comment: Microarrays, Empirical Bayes and the Two-…
In this present work, we discuss the Bayesian inference for the bivariate pseudo-exponential distribution. Initially, we assume independent gamma priors and then pseudo-gamma priors for the pseudo-exponential parameters. We are primarily…
In recent years there has been interest in the theory of local computation over probabilistic Bayesian graphical models. In this paper, local computation over Bayes linear belief networks is shown to be amenable to a similar approach.…
Rejoinder to "Is Bayes Posterior just Quick and Dirty Confidence?" by D. A. S. Fraser [arXiv:1112.5582]
This is a discussion on "Sparse graphs using exchangeable random measures" by Francois Caron and Emily B. Fox, published in Journal of the Royal Statistical Society, Series B, 2017.
Comment on ``Performance of Double-Robust Estimators When ``Inverse Probability'' Weights Are Highly Variable'' [arXiv:0804.2958]
We discuss the methods of Evans and Moshonov [Bayesian Analysis 1 (2006) 893--914, Bayesian Statistics and Its Applications (2007) 145--159] concerning checking for prior-data conflict and their relevance to the method proposed in this…
Empirical Bayes methods use the data from parallel experiments, for instance, observations $X_k\sim\mathcal{N}(\Theta_k,1)$ for $k=1,2,\ldots,N$, to estimate the conditional distributions $\Theta_k|X_k$. There are two main estimation…
This is a Reply to the Comment of S.R. White and D.J. Scalapino [cond-mat/9907243] on our recent paper ``Stripes and the t-J Model'' [Physical Review Letters 83, 132 (1999) and cond-mat/9812022].
I congratulate all the authors for their insightful papers with wide-ranging contributions. The articles demonstrate the power and elegance of the Bayesian inference paradigm. In particular, it allows to incorporate prior knowledge as well…
In this Comment we discuss some points concerning the modeling of parked cars proposed in the article by Rawal and Rodgers, Physica A (2005). We also introduce another approach to this problem which leads to a better description of the…
The article is taken out.
This is an annotated bibliography on estimation and inference results for queues and related stochastic models. The purpose of this document is to collect and categorise works in the field, allowing for researchers and practitioners to…
We propose a Machine Learning approach for optimal macroeconomic density forecasting in a high-dimensional setting where the underlying model exhibits a known group structure. Our approach is general enough to encompass specific forecasting…
Work in progress concerning alternative formalizations of arithmetic.
This is a survey, intended both for group theorists and model theorists, concerning the structure of pseudofinite groups, that is, infinite models of the first order theory of finite groups. The focus is on concepts from stability theory…
Comments on the article "Pulsar dynamics: magnetic dipole model revisited".
This paper is an introduction to the modelling of viscoelastic fluids, with an emphasis on micro-macro (or multiscale) models. Some elements of mathematical and numerical analysis are provided. These notes closely follow the lectures…
We develop a model-based empirical Bayes approach to variable selection problems in which the number of predictors is very large, possibly much larger than the number of responses (the so-called 'large p, small n' problem). We consider the…
Introduction to papers on the modeling and analysis of network data---II
The survey contains a brief description of the ideas, constructions, results, and prospects of the theory of hypergroups and generalized translation operators. Representations of hypergroups are considered, being treated as continuous…