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Related papers: Constructions for a bivariate beta distribution

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The theory of commutative monads on cartesian closed categories provides a framework where aspects of the theory of distributions and other extensive quantities can be formulated and some results proved. We make explicit a link between our…

Category Theory · Mathematics 2011-08-31 Anders Kock

The joint distribution of two off-diagonal Wishart matrix elements was useful in recent work on geometric probability [Finch 2010]. Not finding such formulas in the literature, we report these here.

Statistics Theory · Mathematics 2015-12-18 Steven Finch

The bivariate normal density with unit variance and correlation $\rho$ is well-known. We show that by integrating out $\rho$, the result is a function of the maximum norm. The Bayesian interpretation of this result is that if we put a…

Statistics Theory · Mathematics 2015-11-20 Kai Zhang , Lawrence D. Brown , Edward George , Linda Zhao

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we…

Probability · Mathematics 2018-09-19 Christian Meyer

Counterfactual explanations utilize feature perturbations to analyze the outcome of an original decision and recommend an actionable recourse. We argue that it is beneficial to provide several alternative explanations rather than a single…

Machine Learning · Computer Science 2023-01-24 Natraj Raman , Daniele Magazzeni , Sameena Shah

In this paper we introduce a new probability distribution on (0,1), associated with the I-function, namely, the I-function distribution. This distribution generalizes several known distributions with positive support. It is also shown that…

Probability · Mathematics 2015-03-09 P. Vellaisamy , K. K. Kataria

A significant obstacle in the development of robust machine learning models is covariate shift, a form of distribution shift that occurs when the input distributions of the training and test sets differ while the conditional label…

Machine Learning · Statistics 2021-11-17 Nilesh Tripuraneni , Ben Adlam , Jeffrey Pennington

We define the beta diffusion tree, a random tree structure with a set of leaves that defines a collection of overlapping subsets of objects, known as a feature allocation. A generative process for the tree structure is defined in terms of…

Machine Learning · Statistics 2015-04-06 Creighton Heaukulani , David A. Knowles , Zoubin Ghahramani

Predicting the winner of an election is of importance to multiple stakeholders. To formulate the problem, we consider an independent sequence of categorical data with a finite number of possible outcomes in each. The data is assumed to be…

Applications · Statistics 2024-10-17 Soudeep Deb , Rishideep Roy , Shubhabrata Das

We introduce a new model for sums of exchangeable binary random variables. The proposed distribution is an approximation to the exact distributional form, and relies on the theory of completely monotone functions and the Laplace transform…

Methodology · Statistics 2020-11-18 Ryan Elmore

We introduce a new distribution with support on (0,1) called unifed. It can be used as the response distribution for a GLM and it is suitable for data aggregation. We make a comparison to the beta regression. A link to an R package for…

Applications · Statistics 2019-10-24 Oscar Alberto Quijano Xacur

Pre-validation is a way to build prediction model with two datasets of significantly different feature dimensions. Previous work showed that the asymptotic distribution of the resulting test statistic for the pre-validated predictor…

Methodology · Statistics 2025-05-23 Jing Shang , Sourav Chatterjee , Trevor Hastie , Robert Tibshirani

In our recent works, we developed a probabilistic framework for structural analysis in undirected networks. The key idea of that framework is to sample a network by a symmetric bivariate distribution and then use that bivariate distribution…

Social and Information Networks · Computer Science 2015-10-19 Cheng-Shang Chang , Duan-Shin Lee , Li-Heng Liou , Sheng-Min Lu , Mu-Huan Wu

We are concerned with obtaining well-calibrated output distributions from regression models. Such distributions allow us to quantify the uncertainty that the model has regarding the predicted target value. We introduce the novel concept of…

Machine Learning · Statistics 2019-05-16 Hao Song , Tom Diethe , Meelis Kull , Peter Flach

We introduce in this paper a new generalization of the flexible Weibull distribution with four parameters. This model based on the Beta generalized (BG) distribution, Eugene et al. \cite{Eugeneetal2002}, they first using the BG distribution…

Statistics Theory · Mathematics 2017-03-20 Beih S. El-Desouky , Abdelfattah Mustafa , Shamsan AL-Garash

In a recent article a generalization of the binomial distribution associated with a sequence of positive numbers was examined. The analysis of the nonnegativeness of the formal expressions was a key-point to allow to give them a statistical…

Mathematical Physics · Physics 2015-06-04 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

In this paper, we extend Beta distribution to 2 by 2 matrix and give the analytical formula for its moments. Our analytical formula can be used to analyze the asymptotic behavior of Beta distribution for 2 by 2 matrix.

Applications · Statistics 2020-09-15 Feng Zhao

We consider estimation of the structural distribution function of the cell probabilities of a multinomial sample in situations where the number of cells is large. We review the performance of the natural estimator, an estimator based on…

Statistics Theory · Mathematics 2007-06-13 B. van Es , C. A. J. Klaassen , R. M. Mnatsakanov

We aim to introduce a new extension of beta function and to study its important properties. Using this definition, we introduce and investigate new extended hypergeometric and confluent hypergeometric functions. Further, some hybrid…

Classical Analysis and ODEs · Mathematics 2019-01-23 N. U. Khan , T. Usman , M. Aman

Given a probability distribution $\mu$ a set $\Lambda (\mu)$ of positive real numbers is introduced, so that $\Lambda (\mu)$ measures the "divisibility" of $\mu$. The basic properties of $\Lambda (\mu)$ are described and examples of…

Probability · Mathematics 2007-05-23 S. Albeverio , H. Gottschalk , J. -L. Wu