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We prove a general transfer theorem for multivariate random sequences with independent random indexes in the double array limit setting. We also prove its partial inverse providing necessary and sufficient conditions for the convergence of…

Probability · Mathematics 2016-11-04 V. Yu. Korolev , A. I. Zeifman

There is currently a renewed interest in the Bayesian predictive approach to statistics. This paper offers a review on foundational concepts and focuses on predictive modeling, which by directly reasoning on prediction, bypasses inferential…

Statistics Theory · Mathematics 2024-11-22 Sandra Fortini , Sonia Petrone

In [Fortini et al., Stoch. Proc. Appl. 100 (2002), 147--165] it is demonstrated that a recurrent Markov exchangeable process in the sense of Diaconis and Freedman is essentially a partially exchangeable process in the sense of de Finetti.…

Probability · Mathematics 2009-10-06 Davide Di Cecco

In this paper, double commutativity and the reverse order law for the core inverse are considered. Then, new characterizations of the Moore-Penrose inverse of a regular element are given by one-sided invertibilities in a ring. Furthermore,…

Rings and Algebras · Mathematics 2019-02-20 Jianlong Chen , Huihui Zhu , Pedro Patricio , Yulin Zhang

A new characterization of the exponential distribution is obtained. It is based on an equation involving randomly shifted (translated) order statistics. No specific distribution is assumed for the shift random variables. The proof uses a…

Probability · Mathematics 2017-01-05 Santanu Chakraborty , George P. Yanev

A standard assumption in machine learning is the exchangeability of data, which is equivalent to assuming that the examples are generated from the same probability distribution independently. This paper is devoted to testing the assumption…

Machine Learning · Computer Science 2012-06-29 Valentina Fedorova , Alex Gammerman , Ilia Nouretdinov , Vladimir Vovk

We provide simple examples of two-color exchangeable sequences $\xi=(\xi_1, \xi_2, \ldots, \xi_n)$ that are not exchangeable. This answers a question of Bladt and Shaiderman~\cite[Question 2.6]{bladt2019characterisation} for finite…

Probability · Mathematics 2023-10-04 Raghavendra Tripathi

In this article, we propose a new three parameter distribution by compounding negative binomial with reciprocal inverse Gaussian model called negative binomial-reciprocal inverse Gaussian distribution. This model is tractable with some…

Methodology · Statistics 2019-06-10 Ishfaq Shah Ahmad , Anwar Hassan , Peer Bilal Ahmad

An elementary proof of the two-sidedness of the matrix-inverse is given using only linear independence and the reduced row-echelon form of a matrix. In addition, it is shown that a matrix is invertible if and only if it is row-equivalent to…

History and Overview · Mathematics 2018-08-15 Pietro Paparella

For a Markov chain both the detailed balance condition and the cycle Kolmogorov condition are algebraic binomials. This remark suggests to study reversible Markov chains with the tool of Algebraic Statistics, such as toric statistical…

Statistics Theory · Mathematics 2011-03-31 Giovanni Pistone , Maria Piera Rogantin

Predictive constructions are a powerful way of characterizing the probability law of stochastic processes with certain forms of invariance, such as exchangeability or Markov exchangeability. When de Finetti-like representation theorems are…

Methodology · Statistics 2015-11-16 Sandra Fortini , Sonia Petrone

We introduce and study the permanence properties of the class of linear transfers between probability measures. This class contains all cost minimizing mass transports, but also martingale mass transports, the Schrodinger bridge associated…

Analysis of PDEs · Mathematics 2018-10-29 Malcolm Bowles , Nassif Ghoussoub

We define a conjugate prior for the reversible Markov chain of order $r$. The prior arises from a partially exchangeable reinforced random walk, in the same way that the Beta distribution arises from the exchangeable Poly\'{a} urn. An…

Statistics Theory · Mathematics 2011-05-16 Sergio Bacallado

Iterative imputation, in which variables are imputed one at a time each given a model predicting from all the others, is a popular technique that can be convenient and flexible, as it replaces a potentially difficult multivariate modeling…

Statistics Theory · Mathematics 2012-04-04 Jingchen Liu , Andrew Gelman , Jennifer Hill , Yu-Sung Su

We give a collection of explicit sufficient conditions for the true martingale property of a wide class of exponentials of semimartingales. We express the conditions in terms of semimartingale characteristics. This turns out to be very…

Mathematical Finance · Quantitative Finance 2016-08-12 David Criens , Kathrin Glau , Zorana Grbac

Let $S$ be a Polish space and $(X_n:n\geq1)$ an exchangeable sequence of $S$-valued random variables. Let $\alpha_n(\cdot)=P(X_{n+1}\in \cdot\mid X_1,\...,X_n)$ be the predictive measure and $\alpha$ a random probability measure on $S$ such…

Probability · Mathematics 2013-07-09 Patrizia Berti , Luca Pratelli , Pietro Rigo

This work concerns results on conditions guaranteeing that certain banded $M$-matrices have banded inverses. As a first goal, a graph theoretic characterization for an off-diagonal entry of the inverse of an $M$-matrix to be positive, is…

General Mathematics · Mathematics 2024-12-30 S. Pratihar , K. C. Sivakumar

Conditions for positive and polynomial recurrence have been proposed for a class of reliability models of two elements with transitions from working state to failure and back. As a consequence, uniqueness of stationary distribution of the…

Probability · Mathematics 2020-05-29 Alexander Veretennikov

The Carlson-Simpson lemma is a combinatorial statement occurring in the proof of the Dual Ramsey theorem. Formulated in terms of variable words, it informally asserts that given any finite coloring of the strings, there is an infinite…

Logic · Mathematics 2018-05-21 Lu Liu , Benoit Monin , Ludovic Patey

Existing tools for explaining complex models and systems are associational rather than causal and do not provide mechanistic understanding. We propose a new notion called counterfactual explainability for causal attribution that is…

Machine Learning · Statistics 2025-10-07 Zijun Gao , Qingyuan Zhao