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Uncertain input of a mathematical model induces uncertainties in the output and probabilistic sensitivity analysis identifies the influential inputs to guide decision-making. Of practical concern is the probability that the output would, or…

Information Theory · Computer Science 2022-07-12 Jiannan Yang

Rejoinder to "Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies" [arXiv:1102.2774]

Methodology · Statistics 2011-02-16 Dan L. Nicolae , Xiao-Li Meng , Augustine Kong

We introduce a new formal model -- based on the mathematical construct of sheaves -- for representing contradictory information in textual sources. This model has the advantage of letting us (a) identify the causes of the inconsistency; (b)…

Computation and Language · Computer Science 2018-01-30 Wlodek Zadrozny , Luciana Garbayo

Diffraction on the slit can be interpreted in accordance with the Heisenberg uncertainty principle. This elementary example hints at the importance of the information theory for the quantum physics. The role played by one particularly…

Quantum Physics · Physics 2007-05-23 Z. Hradil , J. Rehacek

A statistical framework is introduced for a broad class of problems involving synchronization or registration of data across a sensor network in the presence of noise. This framework enables an estimation-theoretic approach to the design…

Networking and Internet Architecture · Computer Science 2010-10-15 Stephen D. Howard , Douglas Cochran , William Moran , Frederick R. Cohen

We highlight the advantages of using simultaneously the Shannon and Fisher information measures in providing a useful form of the uncertainty relation for the position-momentum case. It does not require any Fourier transformation. The…

Chemical Physics · Physics 2019-11-14 Kamal Bhattacharyya , Karabi Halder

We introduce a positive Hermitian operator, the Fisher operator, and use it to examine a measurement process incorporating unitary dynamics and complete measurements. We develop the idea of information complement, the minimization of which…

Quantum Physics · Physics 2009-02-20 Gabriel A. Durkin

The resolution of separation of two elementary signals forming a partially coherent superposition, defined by quantum Fisher information and normalised with respect to detection probabilities, is always limited by the resolution of…

Quantum Physics · Physics 2021-03-15 Zdeněk Hradil , Dominik Koutný , Jaroslav Řeháček

With the internet, a massive amount of information on species abundance can be collected under citizen science programs. However, these data are often difficult to use directly in statistical inference, as their collection is generally…

Applications · Statistics 2015-02-27 Christophe Giraud , Clément Calenge , Camille Coron , Romain Julliard

The dynamics of two variants of quantum Fisher information under decoherence are investigated from a geometrical point of view. We first derive the explicit formulas of these two quantities for a single qubit in terms of the Bloch vector.…

Quantum Physics · Physics 2013-02-27 Wei Zhong , Zhe Sun , Jian Ma , Xiaoguang Wang , Franco Nori

This paper deals with Cram\'er-Rao inequalities in the context of nonextensive statistics and in estimation theory. It gives characterizations of generalized q-Gaussian distributions, and introduces generalized versions of Fisher…

Mathematical Physics · Physics 2012-06-05 J. -F. Bercher

The subject of this paper is a mathematical transition from the Fisher information of classical statistics to the matrix formalism of quantum theory. If the monotonicity is the main requirement, then there are several quantum versions…

Quantum Physics · Physics 2017-08-23 Denes Petz , Catalin Ghinea

The Fisher infinitesimal model is a classical model of phenotypic trait inheritance in quantitative genetics. Here, we prove that it encompasses a remarkable convexity structure which is compatible with a selection function having a convex…

Probability · Mathematics 2025-07-30 Vincent Calvez , David Poyato , Filippo Santambrogio

Mixture distributions are extensively used as a modeling tool in diverse areas from machine learning to communications engineering to physics, and obtaining bounds on the entropy of probability distributions is of fundamental importance in…

Information Theory · Computer Science 2022-12-05 James Melbourne , Saurav Talukdar , Shreyas Bhaban , Mokshay Madiman , Murti V. Salapaka

The statistical mechanics of Gibbs is a juxtaposition of subjective, probabilistic ideas on the one hand and objective, mechanical ideas on the other. In this paper, we follow the path set out by Jaynes, including elements added…

Statistical Mechanics · Physics 2015-11-24 David M. Rogers , Thomas L. Beck , Susan B. Rempe

We study semi-parametric estimation of the population mean when data is observed missing at random (MAR) in the $n < p$ "inconsistency regime", in which neither the outcome model nor the propensity/missingness model can be estimated…

Statistics Theory · Mathematics 2023-09-06 Michael Celentano , Martin J. Wainwright

In the study of Heisenberg's error-disturbance relation, it is commonly believed that the non-unitary change of states hinders us from deducing the information encoded in original states about subsequently measured observable. However, we…

Quantum Physics · Physics 2014-10-30 Liang-Liang Sun , Yong-Shun Song , Zhi-Xin Chen , Cong-Feng Qiao

The main result characterises the equivalence of the Newton-Raphson algorithm and PDE of conservation of electric charge. Based on this equivalence we analyse the properties of the Fisher-scoring method, a variant of Newton's method…

Numerical Analysis · Mathematics 2021-11-23 Minzheng Li

While most useful information theoretic inequalities can be deduced from the basic properties of entropy or mutual information, Shannon's entropy power inequality (EPI) seems to be an exception: available information theoretic proofs of the…

Information Theory · Computer Science 2016-11-17 Olivier Rioul

Maximum likelihood estimates and corresponding confidence regions of the estimates are commonly used in statistical inference. In practice, people often construct approximate confidence regions with the Fisher information at given sample…

Statistics Theory · Mathematics 2021-07-13 Sihang Jiang