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Latent variable models are used to estimate variables of interest quantities which are observable only up to some measurement error. In many studies, such variables are known but not precisely quantifiable (such as "job satisfaction" in…

Machine Learning · Statistics 2012-10-19 Ricardo Silva

A sequential importance sampling algorithm is developed for the distribution that results when a matrix of independent, but not identically distributed, Bernoulli random variables is conditioned on a given sequence of row and column sums.…

Computation · Statistics 2013-01-18 Matthew T. Harrison , Jeffrey W. Miller

If there exists a set of canonical classes on a compact Hamiltonian-$T$-spaces in the sense of Goldin and Tolman, we derive some formulas for certain equivariant structure constants in terms of other equivariant structure constants and the…

Symplectic Geometry · Mathematics 2016-09-29 Ho-Hon Leung

A canonical band theory of non-collinear magnetism is developed and applied to the close packed fcc and bcc crystal structures. Several examples of non-collinear magnetism in the periodic table are seen to be canonical in origin. This is a…

Other Condensed Matter · Physics 2007-05-23 S Shallcross , S Sharma

Cardinality potentials are a generally useful class of high order potential that affect probabilities based on how many of D binary variables are active. Maximum a posteriori (MAP) inference for cardinality potential models is…

Machine Learning · Computer Science 2012-10-19 Daniel Tarlow , Kevin Swersky , Richard S. Zemel , Ryan Prescott Adams , Brendan J. Frey

In this paper, we propose to decompose the canonical parameter of a multinomial model into a set of participant scores and category scores. External information about the participants or the categories can be used to restrict these scores.…

Methodology · Statistics 2025-01-23 Mark de Rooij

We give in this short report a very simple proof that arbitrary random variable with Borelian distribution in separable Banach space belongs with probability one to a pre-image of some linear compact non-random operator.

Probability · Mathematics 2014-10-14 E. Ostrovsky , L. Sirota

More than 10 years ago, Dipper, James and Murphy developped the theory of Specht modules for Hecke algebras of type $B\_n$. More recently, using Lusztig's a-function, Geck and Rouquier showed how to obtain parametrisations of the…

Representation Theory · Mathematics 2007-05-23 Meinolf Geck , Nicolas Jacon

The set of all m-tuples of compatible full conditional distributions on discrete random variables is an algebraic set whose defining ideal is a unimodular toric ideal. We identify the defining polynomials of these ideals with closed walks…

Algebraic Geometry · Mathematics 2007-06-13 Aleksandra B Slavkovic , Seth Sullivant

Free cumulants were introduced as the proper analog of classical cumulants in the theory of free probability. There is a mix of similarities and differences, when one considers the two families of cumulants. Whereas the combinatorics of…

Combinatorics · Mathematics 2015-03-17 Kurusch Ebrahimi-Fard , Frederic Patras

The study of sums of possibly associated Bernoulli random variables has been hampered by an asymmetry between positive correlation and negative correlation. The Conway-Maxwell Binomial (COMB) distribution and its multivariate extension, the…

Methodology · Statistics 2014-04-08 Joseph B. Kadane

We present a parallel between commutative and non-commutative polymorphisms. Our emphasis is the applications to conditional distributions from stochastic processes. In the classical case, both the measures and the positive definite kernels…

Quantum Physics · Physics 2025-01-22 Palle E. T. Jorgensen , James Tian

The aim of this paper is to introduce a new technique for calculation of observables, in particular multiplicity distributions, in various statistical ensembles at finite volume. The method is based on Fourier analysis of the grand…

Nuclear Theory · Physics 2008-12-18 M. Hauer , V. V. Begun , M. I. Gorenstein

Relations between moments and cumulants play a central role in both classical and non-commutative probability theory. The latter allows for several distinct families of cumulants corresponding to different types of independences: free,…

Probability · Mathematics 2023-05-16 A. Celestino , K. Ebrahimi-Fard , F. Patras , D. Perales Anaya

Ten years ago, it was shown that nominal techniques can be used to design coalgebraic data types with variable binding, so that alpha-equivalence classes of infinitary terms are directly endowed with a corecursion principle. We introduce…

Logic in Computer Science · Computer Science 2025-11-05 Rémy Cerda

A canonical system of basic invariants is a system of invariants satisfying a set of differential equations. The properties of a canonical system are related to the mean value property for polytopes. In this article, we naturally identify…

Representation Theory · Mathematics 2018-07-09 Norihiro Nakashima , Shuhei Tsujie

We present a novel Bayesian nonparametric regression model for covariates X and continuous, real response variable Y. The model is parametrized in terms of marginal distributions for Y and X and a regression function which tunes the…

Methodology · Statistics 2015-06-25 Tristan Gray-Davies , Chris Holmes , Francois Caron

We express classical, free, Boolean and monotone cumulants in terms of each other, using combinatorics of heaps, pyramids, Tutte polynomials and permutations. We completely determine the coefficients of these formulas with the exception of…

Combinatorics · Mathematics 2019-07-29 Octavio Arizmendi , Takahiro Hasebe , Franz Lehner , Carlos Vargas

A fractional Hamiltonian formalism is introduced for the recent combined fractional calculus of variations. The Hamilton-Jacobi partial differential equation is generalized to be applicable for systems containing combined Caputo fractional…

Mathematical Physics · Physics 2012-06-19 Agnieszka B. Malinowska , Delfim F. M. Torres

Both Approximate Bayesian Computation (ABC) and composite likelihood methods are useful for Bayesian and frequentist inference, respectively, when the likelihood function is intractable. We propose to use composite likelihood score…

Computation · Statistics 2015-02-25 Erlis Ruli , Nicola Sartori , Laura Ventura
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