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Related papers: Comment: Microarrays, Empirical Bayes and the Two-…

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This report introduces general ideas and some basic methods of the Bayesian probability theory applied to physics measurements. Our aim is to make the reader familiar, through examples rather than rigorous formalism, with concepts such as:…

Data Analysis, Statistics and Probability · Physics 2009-11-10 G. D'Agostini

This report assumes the basics of inverse semigroup theory as described in the first primer but goes on to show how they may be analysed using ideas from category theory.

Category Theory · Mathematics 2020-06-01 Mark V Lawson

We present a novel, scalable and Bayesian approach to modelling the occurrence of pairs of symbols (i,j) drawn from a large vocabulary. Observed pairs are assumed to be generated by a simple popularity based selection process followed by…

Machine Learning · Statistics 2014-09-11 Ulrich Paquet , Noam Koenigstein , Ole Winther

This is an attempt at applied mathematics, a sequel to arXiv:math/0306174. It suggests a particular model for the application in question, based on the binary octahedral group.

Category Theory · Mathematics 2020-03-02 Jack Morava

We comment on Z. D. Zhang's Response [arXiv:0812.2330] to our recent Comment [arXiv:0811.3876] addressing the conjectured solution of the three-dimensional Ising model reported in [arXiv:0705.1045].

Statistical Mechanics · Physics 2009-11-13 F. Y. Wu , B. M. McCoy , M. E. Fisher , L. Chayes

The analysis of data from multiple experiments, such as observations of several individuals, is commonly approached using mixed-effects models, which account for variation between individuals through hierarchical representations. This makes…

Computation · Statistics 2026-03-05 Henrik Häggström , Sebastian Persson , Marija Cvijovic , Umberto Picchini

This paper builds on recent research that focuses on regression modeling of continuous bounded data, such as proportions measured on a continuous scale. Specifically, it deals with beta regression models with mixed effects from a Bayesian…

Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a…

Methodology · Statistics 2022-03-04 Se Yoon Lee

This chapter surveys advances in the field of Bayesian computation over the past twenty years, with missing data. It also contains some novel computational entries on the double-exponential model that may be of interest per se.

Methodology · Statistics 2013-06-12 Christian P. Robert

We consider two bivariate models with two-way interactions in context of risk and queueing theory. The two entities interact with each other by providing assistance but otherwise evolve independently. We focus on certain random quantities…

Probability · Mathematics 2019-11-19 Jevgenijs Ivanovs

Rejoinder of "Treelets--An adaptive multi-scale basis for spare unordered data" [arXiv:0707.0481]

Applications · Statistics 2008-07-28 Ann B. Lee , Boaz Nadler , Larry Wasserman

Discussion on "Brownian distance covariance" by G\'{a}bor J. Sz\'{e}kely, Maria L. Rizzo [arXiv:1010.0297]

Applications · Statistics 2010-10-06 Andrey Feuerverger

Discussion on "Brownian distance covariance" by G\'{a}bor J. Sz\'{e}kely, Maria L. Rizzo [arXiv:1010.0297]

Applications · Statistics 2010-10-06 Leslie Cope

We address the problem of providing inference from a Bayesian perspective for parameters selected after viewing the data. We present a Bayesian framework for providing inference for selected parameters, based on the observation that…

Computation · Statistics 2015-03-13 Daniel Yekutieli

Bi-clustering is a useful approach in analyzing biological data when observations come from heterogeneous groups and have a large number of features. We outline a general Bayesian approach in tackling bi-clustering problems in moderate to…

Applications · Statistics 2021-02-11 Han Yan , Jiexing Wu , Yang Li , Jun S. Liu

When opinion spread is studied, peer pressure is often modeled by interactions of more than two individuals (higher-order interactions). In our work, we introduce a two-layer random hypergraph model, in which hyperedges represent households…

Social and Information Networks · Computer Science 2025-12-30 Ágnes Backhausz , Villő Csiszár , Balázs Csegő Kolok , Damján Tárkányi , András Zempléni

Exchangeable arrays are natural tools to model common forms of dependence between units of a sample. Jointly exchangeable arrays are well suited to dyadic data, where observed random variables are indexed by two units from the same…

Statistics Theory · Mathematics 2023-04-18 Laurent Davezies , Xavier D'Haultfoeuille , Yannick Guyonvarch

Discussion of "Instrumental Variables: An Econometrician's Perspective" by Guido W. Imbens [arXiv:1410.0163].

Methodology · Statistics 2016-08-10 Sonja A. Swanson , Miguel A. Hernán

The abstract will be added in due course.

Logic · Mathematics 2019-11-01 Paola D'Aquino , Jamshid Derakhshan , Angus Macintyre

Some practical results are derived for population inference based on a sample, under the two qualitative conditions of 'ignorability' and exchangeability. These are the 'Histogram Theorem', for predicting the outcome of a non-sampled member…

Statistics Theory · Mathematics 2015-11-12 Jonathan Rougier