Related papers: Rejoinder
The natural habitat of most Bayesian methods is data represented by exchangeable sequences of observations, for which de Finetti's theorem provides the theoretical foundation. Dirichlet process clustering, Gaussian process regression, and…
Gene and protein networks are very important to model complex large-scale systems in molecular biology. Inferring or reverseengineering such networks can be defined as the process of identifying gene/protein interactions from experimental…
The style of mathematical models known to probabilists as Interacting Particle Systems and exemplified by the Voter, Exclusion and Contact processes have found use in many academic disciplines. In many such disciplines the underlying…
The present review is based on the lectures that the author had been giving during several years at the Swiss Federal Institute of Technology in Zurich (ETH Zurich). Being bounded by lecture frames, the selection of the material, by…
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
Discussion of ``Breakdown and groups'' by P. L. Davies and U. Gather [math.ST/0508497]
According to Hansen, Madow and Tepping [J. Amer. Statist. Assoc. 78 (1983) 776--793], "Probability sampling designs and randomization inference are widely accepted as the standard approach in sample surveys." In this article, reasons are…
Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical…
Bayesian network is a complete model for the variables and their relationships, it can be used to answer probabilistic queries about them. A Bayesian network can thus be considered a mechanism for automatically applying Bayes' theorem to…
The number of recurrent events before a terminating event is often of interest. For instance, death terminates an individual's process of rehospitalizations and the number of rehospitalizations is an important indicator of economic cost. We…
Disease models are used to examine the likely impact of therapies, interventions and public policy changes. Ensuring that these are well calibrated on the basis of available data and that the uncertainty in their projections is properly…
Comment on paper by Blanchette and Zhang, Phys. Rev. Lett. 102, 144501 (2009).
In this paper we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior…
This paper has been withdrawn. With the advancement of statistical theory and computing power, data sets are providing a greater amount of insight into the problems of today. Statisticians have an ever increasing number of tools to attack…
The Ising model, originally developed for understanding magnetic phase transitions, has become a cornerstone in the study of collective phenomena across diverse disciplines. In this review, we explore how Ising and Ising-like models have…
Comments on the results presented at the Conference "Frontiers Beyond the Standard Model," FTPI, Oct. 2012. This summary traces a historical perspective. v2: A reference corrected and a footnote added; v3: a few grammar mistakes and typos…