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Does the asymptotic variance of the maximum composite likelihood estimator of a parameter of interest always decrease when the nuisance parameters are known? Will a composite likelihood necessarily become more efficient by incorporating…

Statistics Theory · Mathematics 2016-12-22 Ximing Xu , Nancy Reid , Libai Xu

We introduce a method for testing quantum correlations in terms of quasiprobability functions in the presence of noise. We analyze the effects of measurement imperfection and thermal environment on quantum correlations and show that their…

Quantum Physics · Physics 2020-07-09 Seung-Woo Lee , Jaewan Kim , Wonmin Son

An extensive study of the effects of correlations on both charged and neutral current weak interaction rates in dense matter is performed. Both strong and electromagnetic correlations are considered.The propagation of particle-hole…

Astrophysics · Physics 2011-05-05 Sanjay Reddy , Madappa Prakash , James M. Lattimer , Jose A. Pons

Economic models may exhibit incompleteness depending on whether or not they admit certain policy-relevant features such as strategic interaction, self-selection, or state dependence. We develop a novel test of model incompleteness and…

Econometrics · Economics 2023-09-08 Shuowen Chen , Hiroaki Kaido

We present exact results, as well as some illustrative Monte Carlo simulations, concerning a stochastic network with weighted connections in which the fraction of nodes that are dynamically synchronized is a parameter. This allows one to…

Disordered Systems and Neural Networks · Physics 2007-05-23 J. Marro , J. J. Torres , J. M. Cortes , B. Wemmenhove

In this paper we provide a comprehensive study of statistical inference in linear and allied models which exhibit some analytic perturbations in their design and covariance matrices. We also indicate a few potential applications. In the…

Statistics Theory · Mathematics 2008-12-18 Jerzy A. Filar , Irene Hudson , Thomas Mathew , Bimal Sinha

We address the problem of identifying linear relations among variables based on noisy measurements. This is, of course, a central question in problems involving "Big Data." Often a key assumption is that measurement errors in each variable…

Systems and Control · Computer Science 2013-04-16 Lipeng Ning , Tryphon T. Georgiou , Allen Tannenbaum , Stephen P. Boyd

A perturbative approach is used to quantify the effect of noise in data points on fitted parameters in a general homogeneous linear model, and the results applied to the case of conic sections. There is an optimal choice of normalisation…

Computer Vision and Pattern Recognition · Computer Science 2016-11-22 Matthew Collett

We discuss the impact of ideas of open quantum systems and quantum information to various facets of neutrino and neutral meson oscillations. These oscillations are characterized by a number of quantum correlations, both spatial as well as…

High Energy Physics - Phenomenology · Physics 2024-12-05 Subhashish Banerjee

The phenomenology of massive neutrinos -- flavour mixing in the lepton sector causing oscillations between different neutrino-types along their propagation over macroscopic distances in vacuum -- aims at relating observable quantities…

High Energy Physics - Phenomenology · Physics 2020-12-11 Winfried A. Mitaroff

This work models the interconnection of company's investment managers' representations and the market attraction of its shares. The models that reflect the connection of the company's market effectiveness indices and parameters of its…

Portfolio Management · Quantitative Finance 2015-09-17 Valery Vilisov

In this paper, we explain the reasons behind constraint interaction, which is the phenomenon that the results of testing equality constraints may depend heavily on the scaling method used. We find that the scaling methods interfere with the…

Methodology · Statistics 2018-05-01 Stefan Klößner , Eric Klopp

Learning models have been shown to rely on spurious correlations between non-predictive features and the associated labels in the training data, with negative implications on robustness, bias and fairness. In this work, we provide a…

Machine Learning · Statistics 2025-05-29 Simone Bombari , Marco Mondelli

We explore the possibility of putting constraints on quintessence models with large-scale structure observations. In particular we compute the linear and second order growth rate of the fluctuations in different flavors of quintessence…

Astrophysics · Physics 2009-11-06 K. Benabed , F. Bernardeau

Using Random Matrix Theory one can derive exact relations between the eigenvalue spectrum of the covariance matrix and the eigenvalue spectrum of its estimator (experimentally measured correlation matrix). These relations will be used to…

Statistical Mechanics · Physics 2009-11-10 Zdzislaw Burda , Jerzy Jurkiewicz

A theory of correlations between N photons of given frequencies and detected at given time delays is presented. These correlation functions are usually too cumbersome to be computed explicitly. We show that they are obtained exactly through…

Large language models with a huge number of parameters, when trained on near internet-sized number of tokens, have been empirically shown to obey neural scaling laws: specifically, their performance behaves predictably as a power law in…

Machine Learning · Computer Science 2022-11-01 Alexander Maloney , Daniel A. Roberts , James Sully

We discuss various physics aspects of neutrino oscillation with non-standard interactions (NSI). We formulate a perturbative framework by taking \Delta m^2_{21} / \Delta m^2_{31}, s_{13}, and the NSI elements \epsilon_{\alpha \beta}…

High Energy Physics - Phenomenology · Physics 2009-03-27 Takashi Kikuchi , Hisakazu Minakata , Shoichi Uchinami

The Network Disturbance Model of Doreian (1989) expresses the dependency between observations taken at the vertices of a network by modelling the correlation between neighbouring vertices, using a single correlation parameter $\rho$. It has…

Statistics Theory · Mathematics 2021-05-10 A. D. Barbour , Gesine Reinert

We calculate matter effects on neutrino oscillations relevant for long baseline neutrino oscillation experiments. In particular, we compare the results obtained with simplifying approximations for the density profile in the Earth versus…

High Energy Physics - Phenomenology · Physics 2010-12-13 Irina Mocioiu , Robert Shrock