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In this paper, we show how concentration inequalities for Gaussian quadratic form can be used to propose exact confidence intervals of the Hurst index parametrizing a fractional Brownian motion. Both cases where the scaling parameter of the…

Statistics Theory · Mathematics 2010-06-16 Jean-Christophe Breton , Jean-François Coeurjolly

We introduce a general method, named the h-function method, to unify the constructions of level-alpha exact test and 1-alpha exact confidence interval. Using this method, any confidence interval is improved as follows: i) an approximate…

Statistics Theory · Mathematics 2021-08-27 Weizhen Wang

We propose a construction of frequentist confidence intervals that is effective near unphysical regions and unifies the treatment of two-sided and upper limit intervals. It is rigorous, has coverage, is computationally simple and avoids the…

High Energy Physics - Experiment · Physics 2009-10-31 Mark Mandelkern , Jonas Schultz

We show that the byproducts of the standard training process of a random forest yield not only the well known and almost computationally free out-of-bag point estimate of the model generalization error, but also give a direct path to…

Machine Learning · Statistics 2022-03-14 Paulo C. Marques F

Turing's estimator allows one to estimate the probabilities of outcomes that either do not appear or only rarely appear in a given random sample. We perform a simulation study to understand the finite sample performance of several related…

Statistics Theory · Mathematics 2025-03-19 Jie Chang , Michael Grabchak , Jialin Zhang

A results of numerical procedure for construction of confidence intervals for parameter of Poisson distribution for signal in the presence of background which has Poisson distribution with known value of parameter are presented. It is shown…

Data Analysis, Statistics and Probability · Physics 2007-05-23 S. I. Bityukov , N. V. Krasnikov

The application of Bayesian inference for the purpose of model selection is very popular nowadays. In this framework, models are compared through their marginal likelihoods, or their quotients, called Bayes factors. However, marginal…

Methodology · Statistics 2022-07-27 F. Llorente , L. Martino , E. Curbelo , J. Lopez-Santiago , D. Delgado

This paper outlines a framework for quantifying the prior's contribution to posterior inference in the presence of prior-likelihood discordance, a broader concept than the usual notion of prior-likelihood conflict. We achieve this dual…

Methodology · Statistics 2021-01-08 Matthew Reimherr , Xiao-Li Meng , Dan L. Nicolae

Mutual information is a widely-used information theoretic measure to quantify the amount of association between variables. It is used extensively in many applications such as image registration, diagnosis of failures in electrical machines,…

Computation · Statistics 2021-08-21 Luai Al-Labadi , Forough Fazeli-Asl , Zahra Saberi

The incorporation of systematic uncertainties into confidence interval calculations has been addressed recently in a paper by Conrad et al. (Physical Review D 67 (2003) 012002). In their work, systematic uncertainities in detector…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Gary C. Hill

Let X be a second order random process indexed by a compact interval [0,T]. Assume that n independent realizations of X are observed on a fixed grid of p time points. Under mild regularity assumptions on the sample paths of X, we show the…

Statistics Theory · Mathematics 2011-05-25 David Degras

Reacting against the limitation of statistics to decision procedures, R. A. Fisher proposed for inductive reasoning the use of the fiducial distribution, a parameter-space distribution of epistemological probability transferred directly…

Statistics Theory · Mathematics 2013-03-01 David R. Bickel

A fundamental assumption of classical hypothesis testing is that the significance threshold $\alpha$ is chosen independently from the data. The validity of confidence intervals likewise relies on choosing $\alpha$ beforehand. We point out…

Applications · Statistics 2025-03-11 Jesse Hemerik , Nick W Koning

Practical or scientific considerations often lead to selecting a subset of parameters as ``important.'' Inferences about those parameters often are based on the same data used to select them in the first place. That can make the reported…

Methodology · Statistics 2019-06-04 Yoav Benjamini , Yotam Hechtlinger , Philip B. Stark

In Bayesian theory, the role of information is central. The influence exerted by prior information on posterior outcomes often jeopardizes Bayesian studies, due to the potentially subjective nature of the prior choice. In modeling where a…

Statistics Theory · Mathematics 2024-04-26 Antoine Van Biesbroeck

We consider a general class of empirical-type likelihoods and develop higher order asymptotics with a view to characterizing members thereof that allow the existence of possibly data-dependent probability matching priors ensuring…

Statistics Theory · Mathematics 2008-12-18 Rahul Mukerjee

In this paper, inference for the parametric component of a semiparametric model based on sampling from the posterior profile distribution is thoroughly investigated from the frequentist viewpoint. The higher-order validity of the profile…

Statistics Theory · Mathematics 2009-09-29 Guang Cheng , Michael R. Kosorok

There is a vast body of recent literature on the reliability of communication through noisy channels, the recovery of community structures in the stochastic block model, the limiting behavior of the free entropy in spin glasses and the…

Combinatorics · Mathematics 2022-07-25 Konstantinos Panagiotou , Matija Pasch

In the Gaussian linear regression model (with unknown mean and variance), we show that the standard confidence set for one or two regression coefficients is admissible in the sense of Joshi (1969). This solves a long-standing open problem…

Statistics Theory · Mathematics 2018-09-25 Hannes Leeb , Paul Kabaila

Piecewise constant priors are routinely used in the Bayesian Cox proportional hazards model for survival analysis. Despite its popularity, large sample properties of this Bayesian method are not yet well understood. This work provides a…

Statistics Theory · Mathematics 2023-06-16 Bo Y. -C. Ning , Ismaël Castillo