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Regular variation of a multivariate measure with a Lebesgue density implies the regular variation of its density provided the density satisfies some regularity conditions. Unlike the univariate case, the converse also requires regularity…

Probability · Mathematics 2016-01-12 Tiandong Wang , Sidney I. Resnick

We consider the sums $S(k)=\sum_{n=0}^{\infty}\frac{(-1)^{nk}}{(2n+1)^k}$ and $\zeta(2k)=\sum_{n=1}^{\infty}\frac{1}{n^{2k}}$ with $k$ being a positive integer. We evaluate these sums with multiple integration, a modern technique. First, we…

Probability · Mathematics 2018-11-16 Vivek Kaushik , Daniele Ritelli

Let $M_n$ denote a random symmetric $n \times n$ matrix whose upper diagonal entries are independent and identically distributed Bernoulli random variables (which take values $1$ and $-1$ with probability $1/2$ each). It is widely…

Probability · Mathematics 2019-09-10 Asaf Ferber , Vishesh Jain

The formula for probability density functions (PDFs) has been extended to include PDF for energy dissipation rates in addition to other PDFs such as for velocity fluctuations, velocity derivatives, fluid particle accelerations, energy…

Statistical Mechanics · Physics 2009-11-11 T. Arimitsu , N. Arimitsu

We revisit the question of priors that achieve approximate matching of Bayesian and frequentist predictive probabilities. Such priors may be thought of as providing frequentist calibration of Bayesian prediction or simply as devices for…

Statistics Theory · Mathematics 2008-12-18 Trevor J. Sweeting

We study statistical properties of two-dimensional turbulent flows. Three systems are considered: the Navier-Stokes equation, surface quasi-geostrophic flow, and a model equation for thermal convection in the Earth's mantle. Direct…

chao-dyn · Physics 2009-10-31 Norbert Schorghofer

Exploiting the explicit bijection between the density of singular values and the density of eigenvalues for bi-unitarily invariant complex random matrix ensembles of finite matrix size, we aim at finding the induced probability measure on…

Probability · Mathematics 2026-03-24 Matthias Allard , Mario Kieburg

Two types of parameter dependent generalizations of classical matrix ensembles are defined by their probability density functions (PDFs). As the parameter is varied, one interpolates between the eigenvalue PDF for the superposition of two…

Mathematical Physics · Physics 2007-05-23 Peter J. Forrester , Eric M. Rains

This paper develops upper and lower bounds for the probability of Boolean functions by treating multiple occurrences of variables as independent and assigning them new individual probabilities. We call this approach dissociation and give an…

Artificial Intelligence · Computer Science 2015-06-30 Wolfgang Gatterbauer , Dan Suciu

We generalize the notion of Davenport constants to a `higher degree' and obtain various lower and upper bounds, which are sometimes exact as is the case for certain finite commutative rings of prime power cardinality. Two simple examples…

Combinatorics · Mathematics 2022-02-15 Yair Caro , Benjamin Girard , John R. Schmitt

While the problem of estimating a probability density function (pdf) from its observations is classical, the estimation under additional shape constraints is both important and challenging. We introduce an efficient, geometric approach for…

Methodology · Statistics 2018-04-05 Sutanoy Dasgupta , Debdeep Pati , Ian H. Jermyn , Anuj Srivastava

Often, it is required to estimate the probability that a quantity such as toxicity level, plutonium, temperature, rainfall, damage, wind speed, wave size, earthquake magnitude, risk, etc., exceeds an unsafe high threshold. The probability…

Methodology · Statistics 2019-07-24 Benjamin Kedem , Lemeng Pan , Paul Smith , Chen Wang

Mathematical models based on probability density functions (PDF) have been extensively used in hydrology and subsurface flow problems, to describe the uncertainty in porous media properties (e.g., permeability modelled as random field).…

Fluid Dynamics · Physics 2020-06-01 Matteo Icardi , Marco Dentz

In this paper we study the problem of estimating the alpha-, beta- and phi-mixing coefficients between two random variables, that can either assume values in a finite set or the set of real numbers. In either case, explicit closed-form…

Computation · Statistics 2013-07-04 Mehmet Eren Ahsen , Mathukumalli Vidyasagar

Employing the formalism introduced by Sinai and Yakhot [PRL, 63(18), p. 1962, 1989], we study the probability density functions (pdf's) of decaying passive scalars in periodic domains under the influence of smooth large scale velocity…

Chaotic Dynamics · Physics 2009-11-10 Jai Sukhatme

In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…

Fluid Dynamics · Physics 2010-06-04 J. Bakosi , P. Franzese , Z. Boybeyi

In this paper, we analyse singular values of a large $p\times n$ data matrix $\mathbf{X}_n= (\mathbf{x}_{n1},\ldots,\mathbf{x}_{nn})$ where the column $\mathbf{x}_{nj}$'s are independent $p$-dimensional vectors, possibly with different…

Statistics Theory · Mathematics 2021-08-17 Tianxing Mei , Chen Wang , Jianfeng Yao

Permutations of correlated sequences of random variables appear naturally in a variety of applications such as graph matching and asynchronous communications. In this paper, the asymptotic statistical behavior of such permuted sequences is…

Information Theory · Computer Science 2020-01-22 Farhad Shirani , Siddharth Garg , Elza Erkip

The extraction of a physical law y=yo(x) from joint experimental data about x and y is treated. The joint, the marginal and the conditional probability density functions (PDF) are expressed by given data over an estimator whose kernel is…

Data Analysis, Statistics and Probability · Physics 2007-10-10 I. Grabec

This paper considers the problem of recovering the permutation of an n-dimensional random vector X observed in Gaussian noise. First, a general expression for the probability of error is derived when a linear decoder (i.e., linear estimator…

Information Theory · Computer Science 2021-05-10 Minoh Jeong , Alex Dytso , Martina Cardone
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