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This article presents an overview of a theory for performing temporal smoothing on temporal signals in such a way that: (i) temporally smoothed signals at coarser temporal scales are guaranteed to constitute simplifications of corresponding…

Neurons and Cognition · Quantitative Biology 2023-09-26 Tony Lindeberg

Asymptotic statistical theory for estimating functions is reviewed in a generality suitable for stochastic processes. Conditions concerning existence of a consistent estimator, uniqueness, rate of convergence, and the asymptotic…

Statistics Theory · Mathematics 2018-09-06 Jean Jacod , Michael Sørensen

In this paper we consider a class of non-local in time telegraph equations. Recently, it has been proved that the fundamental solutions of such equations can be interpreted as the probability density function of a stochastic process. We…

Analysis of PDEs · Mathematics 2021-01-20 Francisco Alegría , Juan C. Pozo

We study spectral densities for systems on lattices, which, at a phase transition display, power-law spatial correlations. Constructing the spatial correlation matrix we prove that its eigenvalue density shows a power law that can be…

Mathematical Physics · Physics 2014-11-24 Vinayak , T. Prosen , B. Buca , T. H. Seligman

The difference between Lorentz invariance and Lorentz covariance is discussed in detail. A covariant formalism is developed for the internal space-time symmetry of extended particles, especially in connection with the insightful…

High Energy Physics - Phenomenology · Physics 2007-05-23 Y. S. Kim

A possibility to represent the standard model of fundamental particles covariant derivatives by means of approximate generalized fractional Riemann-Liouville derivatives of multifractal time and space model is shown.

High Energy Physics - Theory · Physics 2007-05-23 L. Ya. Kobelev

The Mat{\'e}rn family of covariance functions has played a central role in spatial statistics for decades, being a flexible parametric class with one parameter determining the smoothness of the paths of the underlying spatial field. This…

Statistics Theory · Mathematics 2022-01-10 M. Bevilacqua , C. Caamaño-Carrillo , E. Porcu

The theory of quasi-arithmetic means is a powerful tool in the study of covariance functions across space-time. In the present study we use quasi-arithmetic functionals to make inferences about the permissibility of averages of functions…

Probability · Mathematics 2007-06-13 E. Porcu , J. Mateu , G. Christakos

A characteristic feature of functional data is the presence of phase variability in addition to amplitude variability. Existing functional regression methods do not handle time variability in an explicit and efficient way. In this paper we…

Methodology · Statistics 2014-04-22 Daniel Gervini

General equations of the unified field theory, obtained using the curved and torsional space-time, are presented. They contain only independent geometrical parameters (metric and connections) of the metric-affine space, and describe the…

General Physics · Physics 2026-01-21 Alex Karpelson

The principle of local covariance which was recently introduced admits a generally covariant formulation of quantum field theory. It allows a discussion of structural properties of quantum field theory as well as the perturbative…

High Energy Physics - Theory · Physics 2007-05-23 Klaus Fredenhagen

The Random Parameters model was proposed to explain the structure of the covariance matrix in problems where most, but not all, of the eigenvalues of the covariance matrix can be explained by Random Matrix Theory. In this article, we…

Statistical Finance · Quantitative Finance 2008-12-02 Camilo Rodrigues Neto , Andr\' e C. R. Martins

Explosive growth in spatio-temporal data and its wide range of applications have attracted increasing interests of researchers in the statistical and machine learning fields. The spatio-temporal regression problem is of paramount importance…

Machine Learning · Computer Science 2020-09-15 Aniruddha Rajendra Rao , Qiyao Wang , Haiyan Wang , Hamed Khorasgani , Chetan Gupta

This article introduces a method for estimating the smoothness of a stationary, isotropic Gaussian random field from irregularly spaced data. This involves novel constructions of higher-order quadratic variations and the establishment of…

Statistics Theory · Mathematics 2015-10-30 Wei-Liem Loh

A new discrete-time shot noise Cox process for spatiotemporal data is proposed. The random intensity is driven by a dependent sequence of latent gamma random measures. Some properties of the latent process are derived, such as an…

Methodology · Statistics 2023-08-17 Federico Bassetti , Roberto Casarin , Matteo Iacopini

Covariance functions and variograms play a fundamental role in exploratory analysis and statistical modelling of spatial and spatio-temporal datasets. In this paper, we construct a new class of spatial covariance functions using the Fourier…

Methodology · Statistics 2021-11-16 Mohammad Ghorbani , Jorge Mateu

In this paper, we study mixed power-exponential moment functionals of nonlinearly perturbed semi-Markov processes in discrete time. Conditions under which the moment functionals of interest can be expanded in asymptotic power series with…

Probability · Mathematics 2016-04-28 Mikael Petersson

The temporal Fokker-Planck equation is analytically integrated in an arbitrary number of spatial dimensions but with the 2D and 3D results highlighted. It is shown that a temporal power-law ansatz for the anisotropic diffusion coefficients…

Classical Physics · Physics 2013-06-27 Billy D. Jones

This article primarily aims to unify the various formalisms of multivariate coefficients of variation, leveraging advanced concepts of generalized means, whether weighted or not, applied to the eigenvalues of covariance matrices. We…

Instrumentation and Detectors · Physics 2024-03-13 Elise Colin , Razvigor Ossikovski

This paper is the first part of our survey on various results about the distribution of exponential type Brownian functionals defined as an integral over time of geometric Brownian motion. Several related topics are also mentioned.

Probability · Mathematics 2007-05-23 Hiroyuki Matsumoto , Marc Yor