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Linear regression is a fundamental and popular statistical method. There are various kinds of linear regression, such as mean regression and quantile regression. In this paper, we propose a new one called distribution regression, which…

Methodology · Statistics 2017-12-27 Xin Chen , Xuejun Ma , Wang Zhou

We develop a higher order generalization of the LQ decomposition and show that this decomposition plays an important role in likelihood-based estimation and testing for separable, or Kronecker structured, covariance models, such as the…

Statistics Theory · Mathematics 2018-06-20 David C. Gerard , Peter D. Hoff

In this paper, different strands of literature are combined in order to obtain algorithms for semi-parametric estimation of discrete choice models that include the modelling of unobserved heterogeneity by using mixing distributions for the…

Methodology · Statistics 2022-12-12 Dietmar Bauer , Sebastian Büscher , Manuel Batram

One of the important problem in reliability analysis is computation of stress-strength reliability. But it is impractical to compute it in certain situations. So the estimation stay as an alternative solution to get an approximate value of…

Methodology · Statistics 2022-12-16 Beenu Thomas , V. M. Chacko

We consider elliptic diffusion problems with a random anisotropic diffusion coefficient, where, in a notable direction given by a random vector field, the diffusion strength differs from the diffusion strength perpendicular to this notable…

Numerical Analysis · Mathematics 2018-02-13 Helmut Harbrecht , Marc Schmidlin

This paper describes the Difference-of-Log-Normals (DLN) distribution. A companion paper makes the case that the DLN is a fundamental distribution in nature, and shows how a simple application of the CLT gives rise to the DLN in many…

Methodology · Statistics 2023-02-14 Robert Parham

Usually, the study of city population distribution has been reduced to power laws. In such analysis, a common practice is to consider cities with more than one hundred thousand inhabitants. Here, we argue that the distribution of cities for…

Statistical Mechanics · Physics 2009-11-07 L. C. Malacarne , R. S. Mendes , E. K. Lenzi

We consider three new classes of exponential dispersion models of discrete probability distributions which are defined by specifying their variance functions in their mean value parameterization. In a previous paper (Bar-Lev and Ridder,…

Methodology · Statistics 2020-04-01 Shaul K. Bar-Lev , Ad Ridder

Much of the theory of estimation for exponential family models, which include exponential-family random graph models (ERGMs) as a special case, is well-established and maximum likelihood estimates in particular enjoy many desirable…

Computation · Statistics 2020-09-07 Christian S. Schmid , David R. Hunter

In the present review we discuss different aspects of the two-photon exchange (TPE) physics in elastic $ep$ scattering, at high $Q^2$ as well as at low $Q^2$. The imaginary part of the TPE amplitude gives rise to beam and target single-spin…

High Energy Physics - Phenomenology · Physics 2021-03-29 Dmitry Borisyuk , Alexander Kobushkin

In probability and statistics, reliable modeling of bivariate continuous characteristics remains a real insurmountable consideration. During analysis of bivariate data, we have to deal with heterogeneity that is present in data. Therefore,…

Methodology · Statistics 2022-06-14 Shikhar Tyagi

The estimation of parameters in the frequency spectrum of a seasonally persistent stationary stochastic process is addressed. For seasonal persistence associated with a pole in the spectrum located away from frequency zero, a new…

Methodology · Statistics 2007-09-04 Emma J. McCoy , Sofia C. Olhede , David A. Stephens

The paper presents a novel asymptotic distribution for a mle when the log--likelihood is strictly concave in the parameter for all data points; for example, the exponential family. The new asymptotic distribution can be seen as a refinement…

Statistics Theory · Mathematics 2021-06-15 Stephen G Walker

Distribution system state estimation (DSSE) plays a crucial role in the real-time monitoring, control, and operation of distribution networks. Besides intensive computational requirements, conventional DSSE methods need high-quality…

Systems and Control · Electrical Eng. & Systems 2024-08-05 Renyou Xie , Xin Yin , Chaojie Li , Guo Chen , Nian Liu , Bo Zhao , Zhaoyang Dong

A general class of models is proposed that is able to estimate the whole predictive distribution of a dependent variable $Y$ given a vector of explanatory variables $\xb$. The models exploit that the strength of explanatory variables to…

Methodology · Statistics 2021-03-25 Gerhard Tutz

We propose and investigate a new estimation method for the parameters of models consisting of smooth density functions on the positive half axis. The procedure is based on a recently introduced characterization result for the respective…

Statistics Theory · Mathematics 2021-06-16 Steffen Betsch , Bruno Ebner , Bernhard Klar

The aim of this paper is to extend Azzalini's method. This extension is done in two stages: consider two dependent and non-identically distributed random variables say $X_1$ and $X_2$; model the dependence between $X_1$ and $X_2$ by a…

Statistics Theory · Mathematics 2018-03-06 Filippo Domma , Božidar V. Popović , Saralees Nadarajah

We discuss one-dimensional stochastic processes defined through the Temperley-Lieb algebra related to the Q=1 Potts model. For various boundary conditions, we formulate a conjecture relating the probability distribution which describes the…

Mathematical Physics · Physics 2009-11-07 Paul A. Pearce , Vladimir Rittenberg , Jan de Gier , Bernard Nienhuis

We study the distributions of the LASSO, SCAD, and thresholding estimators, in finite samples and in the large-sample limit. The asymptotic distributions are derived for both the case where the estimators are tuned to perform consistent…

Statistics Theory · Mathematics 2009-09-07 Benedikt M. Potscher , Hannes Leeb

Data analyses typically rely upon assumptions about missingness mechanisms that lead to observed versus missing data. When the data are missing not at random, direct assumptions about the missingness mechanism, and indirect assumptions…

Methodology · Statistics 2016-03-22 Alexander M Franks , Edoardo M Airoldi , Donald B Rubin