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Galaxies and clusters distributions show two major properties: (i) the positions of galaxies and clusters are characterized by a power law distribution indicating properties with respect to their positions. (ii) The distribution of masses…

Astrophysics · Physics 2009-09-25 Francesco Sylos Labini , Luciano Pietronero

Understanding variable dependence, particularly eliciting their statistical properties given a set of covariates, provides the mathematical foundation in practical operations management such as risk analysis and decision-making given…

Methodology · Statistics 2023-09-06 Yunyun Wang , Tatsushi Oka , Dan Zhu

An analysis of moments and spectra shows that, while the distribution of avalanche areas obeys finite size scaling, that of toppling numbers is universally characterized by a full, nonlinear multifractal spectrum. Rare, large avalanches…

Statistical Mechanics · Physics 2009-10-31 Claudio Tebaldi , Mario De Menech , Attilio L. Stella

For a sample of absolutely bounded i.i.d. random variables with a continuous density the cumulative distribution function of the sample variance is represented by a univariate integral over a Fourier series. If the density is a polynomial…

Statistics Theory · Mathematics 2008-10-10 T. Royen

For a tree Markov random field non-reconstruction is said to hold if as the depth of the tree goes to infinity the information that a typical configuration at the leaves gives about the value at the root goes to zero. The distribution of…

Discrete Mathematics · Computer Science 2011-07-28 Nayantara Bhatnagar , Elitza Maneva

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. On the other hand, such hierarchical…

Machine Learning · Computer Science 2022-01-25 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

In this paper we address the complexity of solving linear programming problems with a set of differential equations that converge to a fixed point that represents the optimal solution. Assuming a probabilistic model, where the inputs are…

Computational Complexity · Computer Science 2007-05-23 Asa Ben-Hur , Joshua Feinberg , Shmuel Fishman , Hava T. Siegelmann

We derive a stochastic representation for the probability distribution on the positive orthant $(0,\infty)^d$ whose association between components is minimal among all probability laws with $\ell_p$-norm symmetric survival functions. It is…

Probability · Mathematics 2021-04-07 Jan-Frederik Mai , Ruodu Wang

In this paper we introduce a new parametric distribution, the Mixed Tempered Stable. It has the same structure of the Normal Variance Mean Mixtures but the normality assumption leaves place to a semi-heavy tailed distribution. We show that,…

Statistical Finance · Quantitative Finance 2014-05-30 Edit Rroji , Lorenzo Mercuri

The two dimensional BTW model of SOC, with probabilistically nonuniform distribution of particles among the nearest neighbouring sites, is studied by computer simulation. When the value of height variable of a particular site reaches the…

Statistical Mechanics · Physics 2016-09-23 Ajanta Bhowal Acharyya

The recursive and hierarchical structure of full rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is…

Machine Learning · Statistics 2022-03-24 Yuta Nakahara , Shota Saito , Akira Kamatsuka , Toshiyasu Matsushima

Two old conjectures from problem sections, one of which from SIAM Review, concern the question of finding distributions that maximize P(Sn <= t), where Sn is the sum of i.i.d. random variables X1, ..., Xn on the interval [0,1], satisfying…

Probability · Mathematics 2008-08-13 Ludolf E. Meester

The paper is concerned with stochastic approximation procedures having three main characteristics: truncations with random moving bounds, a matrix valued random step-size sequence, and a dynamically changing random regression function. We…

Statistics Theory · Mathematics 2016-11-14 Teo Sharia , Lei Zhong

Introducing the discrete probability distribution by means of the Prabhakar (or the three--parameter Mittag--Leffler) function, we establish explicit expressions for raw and factorial moments and also general fractional order moments.…

Classical Analysis and ODEs · Mathematics 2016-05-09 Tibor K. Pogány , Živorad Tomovski

In this paper a class of optimization problems with uncertain linear constraints is discussed. It is assumed that the constraint coefficients are random vectors whose probability distributions are only partially known. Possibility theory is…

Optimization and Control · Mathematics 2021-11-30 Romain Guillaume , Adam Kasperski , Pawel Zielinski

A class of discrete probability distributions contains distributions with limited support, i.e. possible argument values are limited to a set of numbers (typically consecutive). Examples of such data are results from subjective experiments…

Methodology · Statistics 2019-09-11 Lucjan Janowski , Bogdan Ćmiel , Krzysztof Rusek , Jakub Nawała , Zhi Li

Spaces of convex and concave functions appear naturally in theory and applications. For example, convex regression and log-concave density estimation are important topics in nonparametric statistics. In stochastic portfolio theory, concave…

Probability · Mathematics 2021-05-25 Peter Baxendale , Ting-Kam Leonard Wong

The Scrooge distribution is a probability distribution over the set of pure states of a quantum system. Specifically, it is the distribution that, upon measurement, gives up the least information about the identity of the pure state,…

Quantum Physics · Physics 2018-10-17 William K Wootters

In this paper we show a characterization of the joint spectral radius of a set of matrices as the limit of the $p$-radius of an associated probability distribution when $p$ tends to $\infty$. Allowing the set to have infinitely many…

Optimization and Control · Mathematics 2016-11-04 Masaki Ogura , Clyde F. Martin

The distribution of seismic moment is of capital interest to evaluate earthquake hazard, in particular regarding the most extreme events. We make use of likelihood-ratio tests to compare the simple Gutenberg-Richter power-law distribution…

Data Analysis, Statistics and Probability · Physics 2015-09-07 Isabel Serra , Álvaro Corral
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