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In this paper, we review Fisher information matrices properties in weighted version and discuss inequalities/bounds on it by using reduced weight functions. In particular, an extended form of the Fisher information inequality previously…

Information Theory · Computer Science 2016-02-01 Mark Kelbert , Yuri Suhov , Salimeh Yasaei Sekeh

Point estimators may not exist, need not be unique, and their distributions are not parameter invariant. Generalized estimators provide distributions that are parameter invariant, unique, and exist when point estimates do not. Comparing…

Statistics Theory · Mathematics 2022-11-04 Paul W. Vos

One of the major problems for maximum likelihood estimation in the well-established directional models is that the normalising constants can be difficult to evaluate. A new general method of "score matching estimation" is presented here on…

Statistics Theory · Mathematics 2016-04-29 Kanti V Mardia , John T Kent , Arnab K Laha

I present several new relations between mutual information (MI) and statistical estimation error for a system that can be regarded simultaneously as a communication channel and as an estimator of an input parameter. I first derive a…

Applications · Statistics 2010-10-08 Sudhakar Prasad

As for other latent-variable problems, exact Bayesian analysis is typically not practicable for mixture problems and approximate methods have been developed. Variational Bayes tends to produce approximate posterior distributions for…

Statistics Theory · Mathematics 2026-02-24 Nils Lid Hjort , Mike Titterington

Semiparametric mixture models are parametric models with latent variables. They are defined kernel, $p_\theta(x | z)$, where z is the unknown latent variable, and $\theta$ is the parameter of interest. We assume that the latent variables…

Statistics Theory · Mathematics 2024-12-03 Stefan Franssen , Jeanne Nguyen , Aad van der Vaart

Paired estimation of change in parameters of interest over a population plays a central role in several application domains including those in the social sciences, epidemiology, medicine and biology. In these domains, the size of the…

Machine Learning · Computer Science 2019-12-02 Ramya Korlakai Vinayak , Weihao Kong , Sham M. Kakade

Unbiased estimation for parameters of maximal distribution is a very fundamental problem in the statistical theory of sublinear expectation. In this paper, we proved that the maximum estimator is the largest unbiased estimator for the upper…

Probability · Mathematics 2016-11-28 Hanqing Jin , Shige Peng

In this article we prove a general theorem which establishes the existence of limiting distributions for a wide class of error terms from prime number theory. As a corollary to our main theorem, we deduce previous results of Wintner (1935),…

Number Theory · Mathematics 2013-06-10 Amir Akbary , Nathan Ng , Majid Shahabi

This paper proposes a Bayesian method for estimating the parameters of a normal distribution when only limited summary statistics (sample mean, minimum, maximum, and sample size) are available. To estimate the parameters of a normal…

Methodology · Statistics 2024-11-21 Tomoki Matsumoto

The reconstruction of the parameter of the model by the measurement of the random variable depending on this parameter is one of the main tasks of statistics. In the paper the notion of the statistically dual distributions is introduced.…

Statistics Theory · Mathematics 2007-06-13 S. I. Bityukov , V. V. Smirnova , V. A. Taperechkina

Statistical inference can be performed by minimizing, over the parameter space, the Wasserstein distance between model distributions and the empirical distribution of the data. We study asymptotic properties of such minimum Wasserstein…

Methodology · Statistics 2019-05-13 Espen Bernton , Pierre E. Jacob , Mathieu Gerber , Christian P. Robert

We prove a Bernstein-von Mises theorem for a general class of high dimensional nonlinear Bayesian inverse problems in the vanishing noise limit. We propose a sufficient condition on the growth rate of the number of unknown parameters under…

Statistics Theory · Mathematics 2017-06-06 Yulong Lu

This paper applies a regularization procedure called increasing rearrangement to monotonize Edgeworth and Cornish-Fisher expansions and any other related approximations of distribution and quantile functions of sample statistics. Besides…

Methodology · Statistics 2017-11-23 Victor Chernozhukov , Ivan Fernandez-Val , Alfred Galichon

We consider the processing of statistical samples $X\sim P_\theta$ by a channel $p(y|x)$, and characterize how the statistical information from the samples for estimating the parameter $\theta\in\mathbb{R}^d$ can scale with the mutual…

Information Theory · Computer Science 2021-07-12 Leighton Pate Barnes , Ayfer Ozgur

This note corrects a pretty serious mistake and some inaccuracies in "Consensus and cooperation in networked multi-agent systems" by R. Olfati-Saber, J.A. Fax, and R.M. Murray, published in Vol. 95 of the Proceedings of the IEEE (2007, No.…

Multiagent Systems · Computer Science 2010-06-04 Pavel Chebotarev

This paper considers statistical estimation problems where the probability distribution of the observed random variable is invariant with respect to actions of a finite topological group. It is shown that any such distribution must satisfy…

Machine Learning · Statistics 2015-06-23 Yu-Hui Chen , Dennis Wei , Gregory Newstadt , Marc DeGraef , Jeffrey Simmons , Alfred Hero

We point out that the main theorem of Ref2 := [Adv. Math. 407, Article ID 108564, 22 p. (2022)] is included in the prior research survey Ref1 := [Expo. Math., 40(2), 265-301, 2022]. For context, we also reproduce the rather simple proof…

Functional Analysis · Mathematics 2022-11-10 José Luis Romero

Prior distributions elicited for modelling the natural fluctuations or the uncertainty on parameters of Bayesian fishery population models, can be chosen among a vast range of statistical laws. Since the statistical framework is defined by…

Statistics Theory · Mathematics 2010-10-12 Nicolas Bousquet

This letter presents simple analytical expressions for the spatial and temporal correlation functions in channels with von Mises-Fisher (vMF) scattering. In contrast to previous results, the expressions presented here are exact and based…

Signal Processing · Electrical Eng. & Systems 2024-12-24 Kenan Turbic , Martin Kasparick , Slawomir Stanczak
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