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Related papers: A comparison of methods for confidence intervals

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By employing various empirical estimators for the Mutual Information (MI) measure, we calculate and compare the estimates and their confidence intervals for both normal and non-normal bivariate data samples. We find that certain nonlinear…

Information Theory · Computer Science 2024-10-10 Theo Grigorenko , Leo Grigorenko

This paper proposes a decorrelation-based approach to test hypotheses and construct confidence intervals for the low dimensional component of high dimensional proportional hazards models. Motivated by the geometric projection principle, we…

Machine Learning · Statistics 2014-12-17 Ethan X. Fang , Yang Ning , Han Liu

Suppose that X_1,X_2,...,X_n are independent and identically Bernoulli(theta) distributed. Also suppose that our aim is to find an exact confidence interval for theta that is the intersection of a 1-\alpha/2 upper confidence interval and a…

Statistics Theory · Mathematics 2013-02-28 Paul Kabaila

The behaviors of various confidence/credible interval constructions are explored, particularly in the region of low statistics where methods diverge most. We highlight a number of challenges, such as the treatment of nuisance parameters,…

Data Analysis, Statistics and Probability · Physics 2015-02-04 Steven D. Biller , Scott M. Oser

We consider a linear regression model with regression parameter beta =(beta_1, ..., beta_p) and independent and identically N(0, sigma^2)distributed errors. Suppose that the parameter of interest is theta = a^T beta where a is a specified…

Computation · Statistics 2009-04-17 Paul Kabaila , Khageswor Giri

We consider the task of constructing confidence intervals with differential privacy. We propose two private variants of the non-parametric bootstrap, which privately compute the median of the results of multiple "little" bootstraps run on…

Machine Learning · Statistics 2024-06-05 Karan Chadha , John Duchi , Rohith Kuditipudi

We show that the two-stage minimum description length (MDL) criterion widely used to estimate linear change-point (CP) models corresponds to the marginal likelihood of a Bayesian model with a specific class of prior distributions. This…

Methodology · Statistics 2023-06-09 David Ardia , Arnaud Dufays , Carlos Ordas Criado

When computing a confidence interval for a binomial proportion p one must choose between using an exact interval, which has a coverage probability of at least 1-{\alpha} for all values of p, and a shorter approximate interval, which may…

Statistics Theory · Mathematics 2015-03-11 Måns Thulin

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

This paper considers a proportional hazards model, which allows one to examine the extent to which covariates interact nonlinearly with an exposure variable, for analysis of lifetime data. A local partial-likelihood technique is proposed to…

Statistics Theory · Mathematics 2007-06-13 Jianqing Fan , Huazhen Lin , Yong Zhou

This article explores combinations of weighted bootstraps, like the Bayesian bootstrap, with the bootstrap $t$ method for setting approximate confidence intervals for the mean of a random variable in small samples. For this problem the…

Statistics Theory · Mathematics 2025-08-21 Art B. Owen

What, if anything, should a frequentist say about a single realized confidence interval (CI) and its chance of having covered the parameter? Jerzy Neyman's original answer was to refuse any nondegenerate probability for coverage ex post…

Other Statistics · Statistics 2026-03-06 Scott Lee

Empirical-likelihood-based confidence intervals for a mean were introduced by Owen [Biometrika 75 (1988) 237-249], where at least a finite second moment is required. This excludes some important distributions, for example, those in the…

Statistics Theory · Mathematics 2007-06-13 Liang Peng

A prediction interval covers a future observation from a random process in repeated sampling, and is typically constructed by identifying a pivotal quantity that is also an ancillary statistic. Analogously, a tolerance interval covers a…

Methodology · Statistics 2022-01-19 Geoffrey S Johnson

The evaluation of the error to be attributed to cut efficiencies is a common question in the practice of experimental particle physics. Specifically, the need to evaluate the efficiency of the cuts for background removal, when they are…

Data Analysis, Statistics and Probability · Physics 2009-02-02 Gioacchino Ranucci

Despite their importance in supporting experimental conclusions, standard statistical tests are often inadequate for research areas, like the life sciences, where the typical sample size is small and the test assumptions difficult to…

Methodology · Statistics 2011-04-15 Pietro Berkes , Jozsef Fiser

There is available an ever-increasing variety of procedures for managing uncertainty. These methods are discussed in the literature of artificial intelligence, as well as in the literature of philosophy of science. Heretofore these methods…

Artificial Intelligence · Computer Science 2013-01-30 Henry E. Kyburg , Choh Man Teng

We connect the power of Confidence Intervals in different Frequentist methods to their reliability. We show that in the case of a bounded parameter a biased method which near the boundary has large power in testing the parameter against…

High Energy Physics - Experiment · Physics 2007-05-23 C. Giunti , M. Laveder

A calculator program has been written to give confidence intervals on branching ratios for rare decay modes (or similar quantities) calculated from the number of events observed, the acceptance factor, the background estimate and the…

High Energy Physics - Experiment · Physics 2011-07-19 Roger Barlow

A simple and common type of medical research involves the comparison of one treatment against another. The logical aim should be both to establish which treatment is superior and the strength of evidence supporting this conclusion, a task…

Methodology · Statistics 2022-12-08 Nicholas Adams