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Various measures in two-way contingency table analysis have been proposed to express the strength of association between row and column variables in contingency tables. Tomizawa et al. (2004) proposed more general measures, including…

Methodology · Statistics 2023-07-10 Wataru Urasaki , Tomoyuki Nakagawa , Tomotaka Momozaki , Sadao Tomizawa

Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we…

Machine Learning · Statistics 2014-11-25 Aviv Tamar , Yonatan Glassner , Shie Mannor

This paper derives asymptotic approximations to the power of Cramer-von Mises (CvM) style tests for inference on a finite dimensional parameter defined by conditional moment inequalities in the case where the parameter is set identified.…

Applications · Statistics 2017-07-10 Timothy B. Armstrong

In contingency table analysis, the odds ratio is a commonly applied measure used to summarize the degree of association between two categorical variables, say R and S. Suppose now that for each individual in the table, a vector of…

Methodology · Statistics 2012-11-16 Francis K. C. Hui , Gery Geenens

Stated choice probabilities are increasingly used in conjunction with the random-coefficient model (RCM) to describe individual preferences. They allow survey respondents to express uncertainty about the future or the incompleteness of a…

General Economics · Economics 2025-03-19 Romuald Meango

Mutual information is commonly used as a measure of similarity between competing labelings of a given set of objects, for example to quantify performance in classification and community detection tasks. As argued recently, however, the…

Social and Information Networks · Computer Science 2025-07-17 Maximilian Jerdee , Alec Kirkley , M. E. J. Newman

The vertex v of a graph G is called a 1-critical-vertex for the maximum genus of the graph, or for simplicity called 1-critical-vertex, if G-v is a connected graph and {\deg}M(G - v) = {\deg}M(G) - 1. In this paper, through the joint-tree…

Combinatorics · Mathematics 2012-03-06 Guanghua Dong , Ning Wang , Yuanqiu Huang , Yanpei Liu

Statistical data is often analyzed as a contingency table, sometimes with empty cells called zeros. Such sparse tables can be due to scarse observations classified in numerous categories, as for example in genetic association studies. Thus,…

Statistics Theory · Mathematics 2010-07-28 Audrey Finkler

Statistical data is often analyzed as a contingency table, sometimes with empty cells called zeros. Such sparse tables can be due to scarse observations classified in numerous categories, as for example in genetic association studies. Thus,…

Statistics Theory · Mathematics 2010-07-28 Audrey Finkler

Copula-based Conditional Value at Risk (CCVaR) is defined as an alternative version of the classical Conditional Value at Risk (CVaR) for multivariate random vectors intended to be real-valued. We aim to generalize CCVaR to several…

Portfolio Management · Quantitative Finance 2026-05-13 Andres Mauricio Molina Barreto

This paper introduces a new property of estimators of the strength of statistical association, which helps characterize how well an estimator will perform in scenarios where dependencies between continuous and discrete random variables need…

Machine Learning · Statistics 2021-01-12 Kiran Karra , Lamine Mili

We study the statistical limits of testing and estimation for a rank one deformation of a Gaussian random tensor. We compute the sharp thresholds for hypothesis testing and estimation by maximum likelihood and show that they are the same.…

Probability · Mathematics 2023-06-23 Aukosh Jagannath , Patrick Lopatto , Leo Miolane

In several real-world applications involving decision making under uncertainty, the traditional expected value objective may not be suitable, as it may be necessary to control losses in the case of a rare but extreme event. Conditional…

Machine Learning · Computer Science 2018-08-07 Ravi Kumar Kolla , Prashanth L. A. , Sanjay P. Bhat , Krishna Jagannathan

It is well known that the approximate distribution of the usual test statistic of a goodness-of-fit test is chi-square, with degrees of freedom equal to the number of categories minus 1 (assuming that no parameters are to be estimated --…

Statistics Theory · Mathematics 2014-10-28 Kris Duszak , Jan Vrbik

We assessed several agreement coefficients applied in 2x2 contingency tables, which are commonly applied in research due to dicotomization by the conditions of the subjects (e.g., male or female) or by conveniency of the classification…

Methodology · Statistics 2022-04-14 Paulo Sergio Panse Silveira , Jose Oliveira Siqueira

The Wiener index of a connected graph is the sum of the distances between all pairs of vertices in the graph. It was conjectured that the Wiener index of an $n$-vertex maximal planar graph is at most $\lfloor\frac{1}{18}(n^3+3n^2)\rfloor$.…

Combinatorics · Mathematics 2019-12-09 Debarun Ghosh , Ervin Győri , Addisu Paulos , Nika Salia , Oscar Zamora

This paper describes an improvement in the upper bound for the magnitude of a coefficient of a term in the chromatic polynomial of a general graph. If $a_r$ is the coefficient of the $q^r$ term in the chromatic polynomial $P(G,q)$, where…

Combinatorics · Mathematics 2007-05-23 Shu-Chiuan Chang

The popularity of Conditional Value-at-Risk (CVaR), a risk functional from finance, has been growing in the control systems community due to its intuitive interpretation and axiomatic foundation. We consider a nonstandard optimal control…

Systems and Control · Electrical Eng. & Systems 2022-06-22 Margaret P. Chapman , Michael Fauss , Kevin M. Smith

A problem of goodness-of-fit test for ergodic diffusion processes is presented. In the null hypothesis the drift of the diffusion is supposed to be in a parametric form with unknown shift parameter. Two Cramer-Von Mises type test statistics…

Statistics Theory · Mathematics 2012-03-30 Ilia Negri , Li Zhou

We develop a maximum-likelihood based method for regression in a setting where the dependent variable is a random graph and covariates are available on a graph-level. The model generalizes the well-known $\beta$-model for random graphs by…

Methodology · Statistics 2017-05-24 Johan Wahlström , Isaac Skog , Patricio S. La Rosa , Peter Händel , Arye Nehorai
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