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A new method for analyzing point patterns produced by the evolution of gravitational clustering is presented. The method is taken from the study of molecular liquids, where it has been introduced for making a statistical description of…

Astrophysics · Physics 2009-10-31 R. Valdarnini

In the context of nonparametric regression, we study conditions under which the consistency (and rates of convergence) of estimators built from discretely sampled curves can be derived from the consistency of estimators based on the…

Statistics Theory · Mathematics 2017-05-29 Forzani Liliana , Fraiman Ricardo , Llop Pamela

Radio polarimetry is a three-dimensional statistical problem. The three-dimensional aspect of the problem arises from the Stokes parameters Q, U, and V, which completely describe the polarization of electromagnetic radiation and…

Astrophysics of Galaxies · Physics 2015-05-20 M. M. McKinnon

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

The application of Stochastic Differential Equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we…

Machine Learning · Statistics 2017-08-09 Constantino A. García , Abraham Otero , Paulo Félix , Jesús Presedo , David G. Márquez

We give necessary and sufficient conditions for the existence of a phantom distribution function for a stationary random field on a regular lattice. We also introduce a less demanding notion of a directional phantom distribution, with…

Probability · Mathematics 2020-04-16 Adam Jakubowski , Igor Rodionov , Natalia Soja-Kukieła

Measuring the (causal) direction and strength of dependence between two variables (events), Xi and Xj , is fundamental for all science. Our survey of decades-long literature on statistical dependence reveals that most assume symmetry in the…

Methodology · Statistics 2022-12-01 Hrishikesh Vinod

The statistical analysis of covariance matrix data is considered and, in particular, methodology is discussed which takes into account the non-Euclidean nature of the space of positive semi-definite symmetric matrices. The main motivation…

Applications · Statistics 2009-10-12 Ian L. Dryden , Alexey Koloydenko , Diwei Zhou

The angular measure on the unit sphere characterizes the first-order dependence structure of the components of a random vector in extreme regions and is defined in terms of standardized margins. Its statistical recovery is an important step…

Statistics Theory · Mathematics 2022-10-18 Stéphan Clémençon , Hamid Jalalzai , Stéphane Lhaut , Anne Sabourin , Johan Segers

The velocity distributions of stellar tracers in general exhibit weak non-Gaussianity encoding information on the orbital composition of a galaxy and the underlying potential. The standard solution for measuring non-Gaussianity involves…

Astrophysics of Galaxies · Physics 2020-10-28 Jason L. Sanders , N. Wyn Evans

Probability functions figure prominently in optimization problems of engineering. They may be nonsmooth even if all input data are smooth.This fact motivates the consideration of subdifferentials for such typically just continuous…

Optimization and Control · Mathematics 2017-07-25 Abderrahim Hantoute , René Henrion , Pedro Pérez-Aros

We study the distributional properties of the linear discriminant function under the assumption of normality by comparing two groups with the same covariance matrix but different mean vectors. A stochastic representation for the…

Statistics Theory · Mathematics 2017-05-09 Taras Bodnar , Stepan Mazur , Edward Ngailo , Nestor Parolya

To detect differences between the mean curves of two samples in longitudinal study or functional data analysis, we usually need to partition the temporal or spatial domain into several pre-determined sub-areas. In this paper we apply the…

Methodology · Statistics 2015-05-01 Peirong Xu , Youngjo Lee , Jian Qing Shi

This paper develops methodology for local sensitivity analysis based on directional derivatives associated with spatial processes. Formal gradient analysis for spatial processes was elaborated in previous papers, focusing on distribution…

Statistics Theory · Mathematics 2015-03-31 Maria A. Terres , Alan E. Gelfand

The angular halfspace depth (ahD) is a natural modification of the celebrated halfspace (or Tukey) depth to the setup of directional data. It allows us to define elements of nonparametric inference, such as the median, the inter-quantile…

Statistics Theory · Mathematics 2024-02-14 Stanislav Nagy , Petra Laketa

We consider graphical models based on a recursive system of linear structural equations. This implies that there is an ordering, $\sigma$, of the variables such that each observed variable $Y_v$ is a linear function of a variable specific…

Methodology · Statistics 2019-06-28 Y. Samuel Wang , Mathias Drton

One of the basic aims in science is to unravel the chain of cause and effect of particular systems. Especially for large systems this can be a daunting task. Detailed interventional and randomized data sampling approaches can be used to…

Methodology · Statistics 2016-11-30 Seyed Mahdi Mahmoudi , Ernst Wit

We construct a new family of chance constrained directional models in stochastic data envelopment analysis, generalizing the deterministic directional models and the chance constrained radial models. We prove that chance constrained…

Probability · Mathematics 2024-10-21 Vicente J. Bolos , Rafael Benitez , Vicente Coll-Serrano

This paper extends a recently introduced theory describing particle transport for random statistically homogeneous systems in which the distribution function p(s) for chord lengths between scattering centers is non-exponential. Here, we…

Mathematical Physics · Physics 2016-02-03 Richard Vasques , Edward W. Larsen

We present a theory of quantum work statistics in generic chaotic, disordered Fermi liquid systems within a driven random matrix formalism. By extending P. W. Anderson's orthogonality determinant formula to compute quantum work…

Mesoscale and Nanoscale Physics · Physics 2023-03-16 András Grabarits , Márton Kormos , Izabella Lovas , Gergely Zaránd
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