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The problem of determining the intrinsic quality of a signal processing system with respect to the inference of an unknown deterministic parameter $\theta$ is considered. While the Fisher information measure $F(\theta)$ forms a classical…

Information Theory · Computer Science 2018-05-30 Manuel Stein , Josef A. Nossek

The Fisher-Rao metric from Information Geometry is related to phase transition phenomena in classical statistical mechanics. Several studies propose to extend the use of Information Geometry to study more general phase transitions in…

Statistical Mechanics · Physics 2016-05-04 Omri Har Shemesh , Rick Quax , Alfons G. Hoekstra , Peter M. A. Sloot

This note discusses the problem of choosing between hypotheses in a situation with many, correlated non-normal variables. A new method is introduced to shrink the many variables into a smaller subset of variables with zero mean, unit…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Byron P. Roe

We prove an extended convexity for quantum Fisher information of a mixed state with a given convex decomposition. This convexity introduces a bound which has two parts: i. classical part associated to the Fisher information of the…

Quantum Physics · Physics 2015-04-09 S. Alipour , A. T. Rezakhani

There has been considerable recent interest in the mean-field dynamics of various atom-interferometry schemes designed for precision sensing. In the field of quantum metrology, the standard tools for evaluating metrological sensitivity are…

Quantum Physics · Physics 2016-06-13 Simon A. Haine

In this paper I discuss the relation between the concept of the Fisher metric and the concept of differentiability of a family of probability measures. I compare the concepts of smooth statistical manifolds, differentiable families of…

Differential Geometry · Mathematics 2023-02-14 Hông Vân Lê

We consider torsion in parameter manifolds that arises via conformal transformations of the Fisher information metric, and define it for information geometry of a wide class of physical systems. The torsion can be used to differentiate…

Classical Physics · Physics 2023-08-09 Kunal Pal , Kuntal Pal , Tapobrata Sarkar

Fisher Discriminant Analysis (FDA) is one of the essential tools for feature extraction and classification. In addition, it motivates the development of many improved techniques based on the FDA to adapt to different problems or data types.…

Machine Learning · Computer Science 2022-05-30 Thu Nguyen , Quang M. Le , Son N. T. Tu , Binh T. Nguyen

This paper proposes an alternative approach for constructing invariant Jeffreys prior distributions tailored for hierarchical or multilevel models. In particular, our proposal is based on a flexible decomposition of the Fisher information…

Statistics Theory · Mathematics 2019-04-29 Thaís C. O. Fonseca , Helio S. Migon , Heudson Mirandola

Quantum Fisher information (QFI) plays a vital role in quantum precision measurement, quantum information, many-body physics, and other domains. Obtaining the QFI from experiment for a quantum state reveals insights such as the limits of…

Quantum Physics · Physics 2024-08-26 Qi Liu

In this paper, a new three-parameter lifetime distribution is introduced and many of its standard properties are discussed. These include shape of the probability density function, hazard rate function and its shape, quantile function,…

Methodology · Statistics 2013-08-21 Min Wang

Recently proposed methods in data subset selection, that is active learning and active sampling, use Fisher information, Hessians, similarity matrices based on gradients, and gradient lengths to estimate how informative data is for a…

Machine Learning · Computer Science 2022-11-08 Andreas Kirsch , Yarin Gal

Testing large covariance matrices is of fundamental importance in statistical analysis with high-dimensional data. In the past decade, three types of test statistics have been studied in the literature: quadratic form statistics, maximum…

Statistics Theory · Mathematics 2020-06-02 Xiufan Yu , Danning Li , Lingzhou Xue

The Fisher information matrix (FIM) is a foundational concept in statistical signal processing. The FIM depends on the probability distribution, assumed to belong to a smooth parametric family. Traditional approaches to estimating the FIM…

Computation · Statistics 2015-06-22 Visar Berisha , Alfred O. Hero

Distributions of wave characteristics of ocean waves, such as wave slope, waveheight or wavelength, are an important tool in a variety of oceanographic applications such as safety of ocean structures or in the study of ship stability, as…

Probability · Mathematics 2008-12-18 Sofia Aberg , Igor Rychlik , M. Ross Leadbetter

We present two extended forms of Fisher information that fit well in the context of nonextensive thermostatistics. We show that there exists an interplay between these generalized Fisher information, the generalized $q$-Gaussian…

Mathematical Physics · Physics 2013-06-05 Jean-François Bercher

This study employs the Riesz-Feller fractional derivative to determine Fisher and Shannon parameters for a one-dimensional harmonic oscillator. By deriving the Riesz fractional derivative of the probability density function, we quantify…

Mathematical Physics · Physics 2024-09-19 A. Boumali , K. Zazoua , F. Serdouk

Fisher-information inequalities have recently been used as operational witnesses of nonclassical metrological behavior, but their physical meaning is often tied to a particular narrative, such as, segmented dynamics or discrete…

Quantum Physics · Physics 2026-05-20 Jeongho Bang , Su-Yong Lee

The quantum Fisher information matrix is a central object in multiparameter quantum estimation theory. It is usually challenging to obtain analytical expressions for it because most calculation methods rely on the diagonalization of the…

Quantum Physics · Physics 2021-05-07 Lukas J. Fiderer , Tommaso Tufarelli , Samanta Piano , Gerardo Adesso

The measure of Jensen-Fisher divergence between probability distributions is introduced and its theoretical grounds set up. This quantity, in contrast to the remaining Jensen divergences, is very sensitive to the fluctuations of the…

Information Theory · Computer Science 2013-01-08 P. Sánchez-Moreno , A. Zarzo , J. S. Dehesa