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Title: Stephen Fienberg's influence on algebraic statistics, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: Stephen (Steve) E. Fienberg (1942-2016) was an eminent statistician, whose impact on research, education and the practice of statistics, and...
Show moreStephen (Steve) E. Fienberg (1942-2016) was an eminent statistician, whose impact on research, education and the practice of statistics, and many other fields is astonishing in its breadth. He was a visionary when it came to linking many different areas to address real scientific issues. He professed the importance of statistics in many disciplines, but recognized that true interdisciplinary work requires joining of the expertise across different areas, and it is in this spirit that he helped steer algebraic statistics toward becoming a thriving subject. Many of his favorite topics in the area are covered in this special issue. We are grateful to all authors for contributing to this volume to honor him and his influence on the field. During the preparation of this issue, we learned about the tragic killing of his widow, Joyce Fienberg, during the Tree of Life Synagogue massacre in Pittsburgh, PA on October 27, 2018. This issue is dedicated to their memory.
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Collection: Journal of Algebraic Statistics

Title: Strongly Robust Toric Ideals in Codimension 2, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: A homogeneous ideal is robust if its universal Gr ?obner basis is also a minimal generating set. For toric ideals, one has the stronger...
Show moreA homogeneous ideal is robust if its universal Gr ?obner basis is also a minimal generating set. For toric ideals, one has the stronger definition: A toric ideal is strongly robust if its Graver basis equals the set of indispensable binomials. We characterize the codimension 2 strongly robust toric ideals by their Gale diagrams. This gives a positive answer to a question of Petrovi?, Thoma, and Vladoiu in the case of codimension 2 toric ideals.
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Collection: Journal of Algebraic Statistics

Title: Generalized Fréchet Bounds for Cell Entries in Multidimensional Contingency Tables, Special Volume in honor of memory of S.E.Fienberg
Description: We consider the lattice, L, of all subsets of a multidimensional contingency table and establish the properties of monotonicity and...
Show moreWe consider the lattice, L, of all subsets of a multidimensional contingency table and establish the properties of monotonicity and supermodularity for the marginalization function, n(·), on L. We derive from the supermodularity of n(·) some generalized Fr ́echet inequalities comple- menting and extending inequalities of Dobra and Fienberg. Further, we construct new monotonic and supermodular functions from n(·), and we remark on the connection between supermodularity and some correlation inequalities for probability distributions on lattices. We also apply an inequal- ity of Ky Fan to derive a new approach to Fr ́echet inequalities for multidimensional contingency tables.
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Collection: Journal of Algebraic Statistics

Title: Exact tests to compare contingency tables under quasi-independence and quasi-symmetry, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: In this work we define log-linear models to compare several square contingency tables under the quasi-independence or the quasi-symmetry model...
Show moreIn this work we define log-linear models to compare several square contingency tables under the quasi-independence or the quasi-symmetry model, and the relevant Markov bases are theoretically characterized. Through Markov bases, an exact test to evaluate if two or more tables fit a common model is introduced. Two real-data examples illustrate the use of tehse models in different fields of applications.
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Collection: Journal of Algebraic Statistics

Title: Inference for Ordinal Log-Linear Models Based on Algebraic Statistics, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: Tools of algebraic statistics combined with MCMC algorithms have been used in contingency table analysis for model selection and model fit...
Show moreTools of algebraic statistics combined with MCMC algorithms have been used in contingency table analysis for model selection and model fit testing of log-linear models. However, this approach has not been considered so far for association models, which are special log-linear models for tables with ordinal classification variables. The simplest association model for two-way tables, the uniform (U) association model, has just one parameter more than the independence model and is applicable when both classification variables are ordinal. Less parsimonious are the row (R) and column (C) effect association models, appropriate when at least one of the classification variables is ordinal. Association models have been extended for multidimensional contingency tables as well. Here, we adjust algebraic methods for association models analysis and investigate their eligibility, focusing mainly on two-way tables. They are implemented in the statistical software R and illustrated on real data tables. Finally the algebraic model fit and selection procedure is assessed and compared to the asymptotic approach in terms of a simulation study.
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Collection: Journal of Algebraic Statistics

Title: Cubature Rules and Expected Value of Some Complex Functions, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: The expected value of some complex valued random vectors is computed by means of the indicator function of a designed experiment as known in...
Show moreThe expected value of some complex valued random vectors is computed by means of the indicator function of a designed experiment as known in algebraic statistics. The general theory is set-up and results are obtained for finite discrete random vectors and the Gaussian random vector. The precision space of some cubature rules/designed experiments is determined.
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Collection: Journal of Algebraic Statistics

Title: On Exchangeability in Network Models, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: We derive representation theorems for exchangeable distributions on finite and infinite graphs using elementary arguments based on geometric...
Show moreWe derive representation theorems for exchangeable distributions on finite and infinite graphs using elementary arguments based on geometric and graph-theoretic concepts. Our results elucidate some of the key differences, and their implications, between statistical network models that are finitely exchangeable and models that define a consistent sequence of probability distributions on graphs of increasing size.
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Collection: Journal of Algebraic Statistics

Title: Maximum Likelihood Estimation of the Latent Class Model through Model Boundary Decomposition, Special Volume in honor of memory of S.E.Fienberg
Date: 2019, 2019-04-12
Description: The Expectation-Maximization (EM) algorithm is routinely used for maximum likelihood estimation in latent class analysis. However, the EM...
Show moreThe Expectation-Maximization (EM) algorithm is routinely used for maximum likelihood estimation in latent class analysis. However, the EM algorithm comes with no global guarantees of reaching the global optimum. We study the geometry of the latent class model in order to understand the behavior of the maximum likelihood estimator. In particular, we characterize the boundary stratification of the binary latent class model with a binary hidden variable. For small models, such as for three binary observed variables, we show that this stratification allows exact computation of the maximum likelihood estimator. In this case we use simulations to study the maximum likelihood estimation attraction basins of the various strata and performance of the EM algorithm. Our theoretical study is complemented with a careful analysis of the EM fixed point ideal which provides an alternative method of studying the boundary stratification and maximizing the likelihood function. In particular, we compute the minimal primes of this ideal in the case of a binary latent class model with a binary or ternary hidden random variable.
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Collection: Journal of Algebraic Statistics

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