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Analytical templates for the 4-Point Correlation Function (4PCF) covariance matrix have been developed in the past assuming a Gaussian Random Field (GRF). In this work, we present the second part of the beyond GRF calculation of the 4PCF…

Cosmology and Nongalactic Astrophysics · Physics 2025-09-09 William Ortolá Leonard , Zachary Slepian

We show that the gamma_i-deformation, which was proposed as candidate gauge theory for a non-supersymmetric three-parameter deformation of the AdS/CFT correspondence, is not conformally invariant due to a running double-trace coupling - not…

High Energy Physics - Theory · Physics 2015-04-01 Jan Fokken , Christoph Sieg , Matthias Wilhelm

The gravitational evolution of the cosmic one-point probability distribution function (PDF) has been estimated using an analytic approximation that combines gravitational perturbation theory with the Edgeworth expansion around a Gaussian…

Astrophysics · Physics 2009-10-31 E. Gaztanaga , P. Fosalba , E. Elizalde

In this paper, joint limit distributions of maxima and minima on independent and non-identically distributed bivariate Gaussian triangular arrays is derived as the correlation coefficient of $i$th vector of given $n$th row is the function…

Probability · Mathematics 2016-04-28 Yingying Lu , Zuoxiang Peng

The tails of the distribution of a mean zero, variance $\sigma^2$ random variable $Y$ satisfy concentration of measure inequalities of the form $\mathbb{P}(Y \ge t) \le \exp(-B(t))$ for $$ B(t)=\frac{t^2}{2( \sigma^2 + ct)} \quad \mbox{for…

Probability · Mathematics 2014-11-26 Larry Goldstein , Umit Islak

The large scale gravitational potential distribution and its influence on the large-scale matter clustering is considered on the basis of six simulations. It is found that the mean separation between zero levels of the potential along…

Astrophysics · Physics 2007-05-23 Soeren Madsen , Andrei G. Doroshkevich , Stefan Gottloeber , Volker Müller

We consider covariance estimation in the multivariate generalized Gaussian distribution (MGGD) and elliptically symmetric (ES) distribution. The maximum likelihood optimization associated with this problem is non-convex, yet it has been…

Methodology · Statistics 2015-06-15 Teng Zhang , Ami Wiesel , Maria Sabrina Grec

We prove inequalities on non-integer powers of products of generalized matrices functions on the sum of positive semi-definite matrices. For example, for any real number $r \in \{1\} \cup [2, \infty)$, positive semi-definite matrices $A_i,\…

Functional Analysis · Mathematics 2016-09-01 Shaowu Huang , Chi-Kwong Li , Yiu-Tung Poon , Qing-Wen Wang

In the context of mod-Gaussian convergence, as defined previously in our work with J. Jacod, we obtain lower bounds for local probabilities for a sequence of random vectors which are approximately Gaussian with increasing covariance. This…

Number Theory · Mathematics 2014-02-26 E. Kowalski , A. Nikeghbali

The paper is to prove the Gaussian correlation conjecture stating that, under the standard Gaussian measure, the measure of the intersection of any two symmetric convex sets is greater than or equal to the product of their measures.…

Probability · Mathematics 2013-03-05 Guan Qingyang

We study the probability distribution of the index ${\mathcal N}_+$, i.e., the number of positive eigenvalues of an $N\times N$ Gaussian random matrix. We show analytically that, for large $N$ and large $\mathcal{N}_+$ with the fraction…

Statistical Mechanics · Physics 2015-03-17 Satya N. Majumdar , Céline Nadal , Antonello Scardicchio , Pierpaolo Vivo

We consider Gaussian distributions on certain Riemannian symmetric spaces. In contrast to the Euclidean case, it is challenging to compute the normalization factors of such distributions, which we refer to as partition functions. In some…

Statistics Theory · Mathematics 2021-05-18 Simon Heuveline , Salem Said , Cyrus Mostajeran

By the results of Furuhata--Inoguchi--Kobayashi [Inf. Geom. (2021)] and Kobayashi--Ohno [Osaka Math. J. (2025)], the Amari--Chentsov $\alpha$-connections on the space $\mathcal{N}$ of all $n$-variate normal distributions are uniquely…

Differential Geometry · Mathematics 2025-04-18 Hikozo Kobayashi , Takayuki Okuda

Let $\BS_1,...,\BS_n$ be independent identically distributed random variables each having the standardized Bernoulli distribution with parameter $p\in(0,1)$. Let $m_*(p):=(1+p+2p^2)/(2\sqrt{p-p^2}+4p^2)$ if $0<p\le 1/2$ and $m_*(p):=1$ if…

Probability · Mathematics 2007-12-23 Iosif Pinelis

A new Riemannian geometry for the Compound Gaussian distribution is proposed. In particular, the Fisher information metric is obtained, along with corresponding geodesics and distance function. This new geometry is applied on a change…

Machine Learning · Statistics 2020-05-21 Florent Bouchard , Ammar Mian , Jialun Zhou , Salem Said , Guillaume Ginolhac , Yannick Berthoumieu

The generalized Marcum functions $Q_{\mu}(x,y)$ and $P_{\mu}(x,y)$ have as particular cases the non-central $\chi^2$ and gamma cumulative distributions, which become central distributions (incomplete gamma function ratios) when the…

Classical Analysis and ODEs · Mathematics 2014-06-25 J. Segura

We have calculated the joint probability distribution function for random reverse-cyclic matrices and shown that it is related to an N-body exactly solvable model. We refer to this well-known model potential as a screened harmonic…

Mathematical Physics · Physics 2013-02-13 Shashi C. L. Srivastava , Sudhir R. Jain

We consider the Gaussian correlation inequality for nonsymmetric convex sets. More precisely, if $A\subset\mathbb{R}^d$ is convex and the origin $0\in A$, then for any ball $B$ centered at the origin, it holds $\gamma_d(A\cap B)\geq…

Probability · Mathematics 2013-01-30 Adrian P. C. Lim , Dejun Luo

An integral over the interval $(0,\pi)$ is given for the cumulative distribution function of a sum of independent gamma random variables with different scale and shape parameters. The cumulative distribution function of a positive definite…

Probability · Mathematics 2024-12-18 Thomas Royen

Statistical divergences are ubiquitous in machine learning as tools for measuring discrepancy between probability distributions. As these applications inherently rely on approximating distributions from samples, we consider empirical…

Statistics Theory · Mathematics 2020-05-01 Ziv Goldfeld , Kengo Kato