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We study general nonlinear models for time series networks of integer and continuous valued data. The vector of high dimensional responses, measured on the nodes of a known network, is regressed non-linearly on its lagged value and on…

Methodology · Statistics 2023-12-25 Mirko Armillotta , Konstantinos Fokianos

Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further…

Methodology · Statistics 2009-11-12 Adelchi Azzalini , Antonella Capitanio

We present a structured additive regression approach to model conditional densities given scalar covariates, where only samples of the conditional distributions are observed. This links our approach to distributional regression models for…

Methodology · Statistics 2025-10-17 Eva-Maria Maier , Alexander Fottner , Sonja Greven , Almond Stöcker

We give an explicit solution formula for the polynomial regression problem in terms of Schur polynomials and Vandermonde determinants. We thereby generalize the work of Chang, Deng, and Floater to the case of model functions of the form…

Rings and Algebras · Mathematics 2026-02-24 Hans-Christian Herbig , Daniel Herden , Christopher Seaton

The distribution of the sum of independent identically distributed uniform random variables is well-known. However, it is sometimes necessary to analyze data which have been drawn from different uniform distributions. By inverting the…

Statistics Theory · Mathematics 2010-05-25 David M. Bradley , Ramesh C. Gupta

A new mathematical model for the dynamics of prion proliferation involving an ordinary differential equation coupled with a partial integro-differential equation is analyzed, continuing earlier work. We show the well-posedness of this…

Analysis of PDEs · Mathematics 2007-05-23 Hans Engler , Jan Pruess , Glenn F. Webb

The paper considers the stationary Poisson Boolean model with spherical grains and proposes a family of nonparametric estimators for the radius distribution. These estimators are based on observed distances and radii, weighted in an…

Probability · Mathematics 2013-01-09 Daniel Hug , Günter Last , Zbyněk Pawlas , Wolfgang Weil

It will be recalled that the classical bivariate normal distributions have normal marginals and normal conditionals. It is natural to ask whether a similar phenomenon can be encountered involving Poisson marginals and conditionals.…

Methodology · Statistics 2020-09-04 Barry C. Arnold , B. G. Manjunath

In this paper, we derive the explicit series expansion of the eigenvalue distribution of various models, namely the case of non-central Wishart distributions, as well as correlated zero mean Wishart distributions. The tools used extend…

Information Theory · Computer Science 2016-11-17 Ø. Ryan , A. Masucci , S. Yang , M. Debbah

This paper explores strong and weak consistency of M-estimators for non-identically distributed data, extending prior work. Emphasis is given to scenarios where data is viewed as a triangular array, which encompasses distributional…

Statistics Theory · Mathematics 2025-11-17 Axel Bücher , Johan Segers , Torben Staud

We constructed a model that evolved from a non-equilibrium state to an equilibrium state. The model only needs two basic coefficients, including self-similar coefficients and non-equilibrium coefficients. The coefficients of the model can…

Statistical Mechanics · Physics 2020-11-24 Zhifu Huang , Yuqing Wang

An implicit Euler finite-volume scheme for a nonlocal cross-diffusion system on the multidimensional torus is analyzed. The equations describe the dynamics of population species with repulsive or attractive interactions. The numerical…

Numerical Analysis · Mathematics 2026-01-06 Ansgar Jüngel , Panchi Li , Zhiwei Sun

We introduce a class of explicit balanced schemes for stochastic differential equations with coefficients of superlinearly growth satisfying a global monotone condition. The first scheme is a balanced Euler scheme and is of order half in…

Numerical Analysis · Mathematics 2017-05-23 Zhongqiang Zhang , Heping Ma

The paper proposes one-to-one transformation of the vector of components $\{Y_{in}\}_{i=1}^m$ of Pearson's chi-square statistic, \[Y_{in}=\frac{\nu_{in}-np_i}{\sqrt{np_i}},\qquad i=1,\ldots,m,\] into another vector $\{Z_{in}\}_{i=1}^m$,…

Statistics Theory · Mathematics 2014-01-06 Estate Khmaladze

Macroscopic fluctuation theory has shown that a wide class of non-equilibrium stochastic dynamical systems obey a large deviation principle, but except for a few one-dimensional examples these large deviation principles are in general not…

Statistical Mechanics · Physics 2014-10-02 Gino Del Ferraro , Erik Aurell

The emergence of non-gaussian distributions for macroscopic quantities in nonequilibrium steady states is discussed with emphasis on the effective criticality and on the ensuing universality of distribution functions. The following problems…

Statistical Mechanics · Physics 2009-11-10 Zoltan Racz

A class of nonequilibrium models with short-range interactions and sequential updates is presented. The models describe one dimensional growth processes which display a roughening transition between a smooth and a rough phase. This…

Condensed Matter · Physics 2009-10-28 Uri Alon , Martin Evans , Haye Hinrichsen , David Mukamel

A simple and transparent derivation of the formally exact probability distribution for classical non-equilibrium systems is given. The corresponding stochastic, dissipative equations of motion are also derived.

Statistical Mechanics · Physics 2014-05-08 Phil Attard

Exponential distributions appear in a wide range of applications including chemistry, nuclear physics, time series analyses, and stock market trends. There are conceivable circumstances in which one would be interested in the cumulative…

History and Overview · Mathematics 2018-03-23 Cecilia Chirenti , M. Coleman Miller

We present a nonparametric framework to model a short sequence of probability distributions that vary both due to underlying effects of sequential progression and confounding noise. To distinguish between these two types of variation and…

Methodology · Statistics 2019-02-08 Jonas Mueller , Tommi Jaakkola , David Gifford
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