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A new method for multinomial inference is proposed by representing the cell probabilities as unordered segments on the unit interval and following Dempster-Shafer (DS) theory. The resulting DS posterior is then strengthened to improve…

Methodology · Statistics 2024-10-10 Earl C. Lawrence , Alexander C. Murph , Scott A. Vander Wiel , Chaunhai Liu

In multiple classification, one aims to determine whether a testing sequence is generated from the same distribution as one of the M training sequences or not. Unlike most of existing studies that focus on discrete-valued sequences with…

Machine Learning · Statistics 2024-10-30 Lina Zhu , Lin Zhou

In this paper we construct general vector-valued infinite-divisible independently scattered random measures with values in $\mathbb{R}^m$ and their corresponding stochastic integrals. Moreover, given such a random measure, the class of all…

Probability · Mathematics 2018-10-17 Dustin Kremer , Hans-Peter Scheffler

Distributions over permutations arise in applications ranging from multi-object tracking to ranking of instances. The difficulty of dealing with these distributions is caused by the size of their domain, which is factorial in the number of…

Machine Learning · Statistics 2010-07-16 Sergey M. Plis , Terran Lane , Vince D. Calhoun

A theorem of McCann shows that for any two absolutely continuous probability measures on R^d there exists a monotone transformation sending one probability measure to the other. A consequence of this theorem, relevant to statistics, is that…

Methodology · Statistics 2015-03-20 Ethan Anderes , Marc Coram

We estimate the derivative of a probability density function defined on $[0,\infty)$. For this purpose, we choose the class of kernel estimators with asymmetric gamma kernel functions. The use of gamma kernels is fruitful due to the fact…

Statistics Theory · Mathematics 2015-02-10 L. A. Markovich

Networks of genetic expression can be modelled by hypergraphs with the additional structure that real coefficients are given to each vertex-edge incidence. The spectra, i.e. the multiset of the eigenvalues, of such hypergraphs, are known to…

Molecular Networks · Quantitative Biology 2021-09-24 Raffaella Mulas , Michael J. Casey

This study proposes a data condensation method for multivariate kernel density estimation by genetic algorithm. First, our proposed algorithm generates multiple subsamples of a given size with replacement from the original sample. The…

Methodology · Statistics 2022-03-04 Kiheiji Nishida

A new methodology is proposed for generating realizations of a random vector with values in a finite-dimensional Euclidean space that are statistically consistent with a data set of observations of this vector. The probability distribution…

Probability · Mathematics 2016-08-24 Christian Soize , Roger Ghanem

The empirical probability density function for the conditional distribution of the true value of Poisson distribution parameter on one measurement is constructed by computer experiment. The analysis of the obtained distributions confirms…

Data Analysis, Statistics and Probability · Physics 2009-11-10 S. I. Bityukov , V. A. Medvedev , V. V. Smirnova , Yu. V. Zernii

Two semimetrics on probability distributions are proposed, given as the sum of differences of expectations of analytic functions evaluated at spatial or frequency locations (i.e, features). The features are chosen so as to maximize the…

Machine Learning · Statistics 2016-10-31 Wittawat Jitkrittum , Zoltan Szabo , Kacper Chwialkowski , Arthur Gretton

The property of perfectness plays an important role in the theory of Bayesian networks. First, the existence of perfect distributions for arbitrary sets of variables and directed acyclic graphs implies that various methods for reading…

Artificial Intelligence · Computer Science 2012-12-12 Christopher Meek , David Maxwell Chickering

We consider uniform random permutations drawn from a family enumerated through generating trees. We develop a new general technique to establish a central limit theorem for the number of consecutive occurrences of a fixed pattern in such…

Probability · Mathematics 2021-12-22 Jacopo Borga

We introduce a new methodology for analyzing serial data by quantile regression assuming that the underlying quantile function consists of constant segments. The procedure does not rely on any distributional assumption besides serial…

Methodology · Statistics 2020-09-09 Laura Jula Vanegas , Merle Behr , Axel Munk

In the idealized Morgan model of crossover, we study the probability distributions of shared DNA (identical by descent) between individuals having a wide range of relationships (not just lineal descendants), especially cases for which…

Genomics · Quantitative Biology 2020-10-08 William H. Press , John Hawkins

Populations of heterogeneous cells play an important role in many biological systems. In this paper we consider systems where each cell can be modelled by an ordinary differential equation. To account for heterogeneity, parameter values are…

Quantitative Methods · Quantitative Biology 2009-09-27 Steffen Waldherr , Jan Hasenauer , Frank Allgöwer

We introduce a complexity measure for symbolic sequences. Starting from a segmentation procedure of the sequence, we define its complexity as the entropy of the distribution of lengths of the domains of relatively uniform composition in…

Classical Physics · Physics 2007-05-23 Ana P. Majtey , Ramon Roman-Roldan , Pedro W. Lamberti

In this work, we derive some novel properties of the bimodal normal distribution. Some of its mathematical properties are examined. We provide a formal proof for the bimodality and assess identifiability. We then discuss the maximum…

Statistics Theory · Mathematics 2021-06-02 Roberto Vila , Helton Saulo , Jamer Roldan

Construction of phylogenetic trees and networks for extant species from their characters represents one of the key problems in phylogenomics. While solution to this problem is not always uniquely defined and there exist multiple methods for…

Populations and Evolution · Quantitative Biology 2016-08-10 Nikita Alexeev , Max A. Alekseyev

Exact formulas are derived for the probability density functions of the sum and difference of two independent non-central gamma distributed random variables, with both series and integral representations of the density presented. These…

Probability · Mathematics 2026-05-18 Robert E. Gaunt , Heather L. Sutcliffe