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A new statistical technique for constructing linear latent structure (LLS) models from available data, supported by well established theoretical results and an efficient algorithm, is presented. The method reduces the problem of estimating…

Statistics Theory · Mathematics 2007-06-13 I. Akushevich , M. Kovtun , A. I. Yashin , K. G. Manton

We propose an alternative approach on the existence of affine realizations for HJM interest rate models. It is applicable to a wide class of models, and simultaneously it is conceptually rather comprehensible. We also supplement some known…

Probability · Mathematics 2019-07-17 Stefan Tappe

Weighted average sampling is more practical and numerically more stable than sampling at single points as in the classical Shannon sampling framework. Using the frame theory, one can completely reconstruct a bandlimited function from its…

Information Theory · Computer Science 2014-07-04 Haizhang Zhang

Given a gamma population with known shape parameter $\alpha$, we develop a general theory for estimating a function $g(\cdot)$ of the scale parameter $\beta$ with bounded variance. We begin by defining a sequential sampling procedure with…

Methodology · Statistics 2024-07-09 Jun Hu , Ibtihal Alanazi , Zhe Wang

Holomorphic functions are amazing because their values in an ever so small disk in the complex plane completely determine the function values at arbitrary points in their maximum possible domain. The process of extending such a function…

Complex Variables · Mathematics 2015-05-15 Stefan Kranich

In science and medicine, model interpretations may be reported as discoveries of natural phenomena or used to guide patient treatments. In such high-stakes tasks, false discoveries may lead investigators astray. These applications would…

Machine Learning · Statistics 2020-08-18 Collin Burns , Jesse Thomason , Wesley Tansey

We have built a new kind of manifolds which leads to an alternative new geometrical space. The study of the nowhere differentiable functions via a family of mean functions leads to a new characterization of this category of functions. A…

General Physics · Physics 2008-11-26 Faycal Ben Adda

Establishing the convergence of splines can be cast as a variational problem which is amenable to a $\Gamma$-convergence approach. We consider the case in which the regularization coefficient scales with the number of observations, $n$, as…

Statistics Theory · Mathematics 2017-03-14 Matthew Thorpe , Adam M. Johansen

We introduce the notion of a restricted exchangeable partition of $\mathbb{N}$. We obtain integral representations, consider associated fragmentations, embeddings into continuum random trees and convergence to such limit trees. In…

Probability · Mathematics 2012-11-12 Bo Chen , Matthias Winkel

In this note I will review some of the recent results that have been obtained in the probabilistic approach to the random satisfiability problem. At the present moment the results are only heuristic. In the case of the random…

Computational Complexity · Computer Science 2007-05-23 Giorgio Parisi

We revisit the classical dual ascent algorithm for minimization of convex functionals in the presence of linear constraints, and give convergence results which apply even for non-convex functionals. We describe limit points in terms of the…

Optimization and Control · Mathematics 2016-09-22 Fredrik Andersson , Marcus Carlsson , Carl Olsson

How predictable a word is can be quantified in two ways: using human responses to the cloze task or using probabilities from language models (LMs).When used as predictors of processing effort, LM probabilities outperform probabilities…

Computation and Language · Computer Science 2026-05-27 Sathvik Nair , Byung-Doh Oh

In this paper, a simulation-based method for the analysis and design of abstracted models for a stochastic hybrid system is proposed. The accuracy of a model is evaluated in terms of its capability to reproduce the system output for all the…

Systems and Control · Computer Science 2014-05-29 M. Prandini , S. Garatti , R. Vignali

In the previous paper "Stabilizing Inverse Problems by Internal Data", the authors introduced a simple procedure that allows one to detect whether and explain why internal information arising in several novel coupled physics (hybrid)…

Analysis of PDEs · Mathematics 2014-11-04 Peter Kuchment , Dustin Steinhauer

We study the structure of an algebraically closed field with extra function resembling the classical exponentiation on complex numbers.

Logic · Mathematics 2007-05-23 Boris Zilber

To contrast different generators for flow equations for Hamiltonians and to discuss the dependence of physical quantities on unitarily equivalent, but effectively different initial Hamiltonians, a numerically solvable model is considered…

Statistical Mechanics · Physics 2009-11-07 T. Stauber , A. Mielke

We compute the analytic expression of the probability distributions F{FTSE100,+} and F{FTSE100,-} of the normalized positive and negative FTSE100 (UK) index daily returns r(t). Furthermore, we define the alpha re-scaled FTSE100 daily index…

Statistical Finance · Quantitative Finance 2010-04-13 Rui Gonçalves , Helena Ferreira , Alberto Pinto

The non-exponential relaxation is shown to result from subordination by inverse tempered \alpha-stable processes. The main feature of tempered \alpha-stable processes is a finiteness of their moments, and the class of random processes…

Statistical Mechanics · Physics 2011-11-15 Aleksander Stanislavsky , Karina Weron

This paper introduces a new term rewriting system that is similar to the embedded read-back mechanism for interaction nets presented in our previous work, but is easier to follow than in the original setting and thus to analyze its…

Logic in Computer Science · Computer Science 2018-08-21 Anton Salikhmetov

Lanchester's model of combat has certain deficiencies in its standard form arising from the neglect of the influence of random fluctuations. Several approaches to rectify this have been proposed and various results are scattered throughout…

Physics and Society · Physics 2019-05-09 Michael J. Kearney , Richard J. Martin