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Improved approximations for confidence distributions

2016
Previous chapters have developed concepts and methodology pertaining to confidence distributions and related inference procedures. Some of these methods take the form of generally applicable recipes, via log-likelihood profiles, deviances and first-order large-sample approximations to the distribution of estimators of the focus estimands in question ...
Tore Schweder, Nils Lid Hjort
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Advances in confidence distribution [PDF]

open access: possible, 2017
In this dissertation, we develop new methods for problems for the two fundamental topics of statistical learning - inference and prediction, using the tool of confidence distribution (CD). Specifically, we are interested in i) making efficient and valid statistical inference about an individual subject, by borrowing information from other individual ...
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Can Bayesian, confidence distribution and frequentist inference agree?

Statistical Methods & Applications, 2020
E. Ruli, L. Ventura
semanticscholar   +1 more source

A new confidence region for the multinomial distribution

Communications in Statistics - Simulation and Computation, 2015
ABSTRACTA simple confidence region is proposed for the multinomial parameter. It is designed for situations having zero cell counts. Simulation studies as well as a real data application show that it performs at least as well as than at least two of the most common confidence regions.
Saralees Nadarajah   +1 more
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High Confidence Reconfigurable Distributed Control

2005
Abstract : The Caltech/Colorado SEC project developed and tested two major advances in software enabled control: optimization-based control using real-time trajectory generation and logical programming environments for formal analysis of distributed control systems.
Jay Hauser   +2 more
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Tables of Confidence Limits for the Binomial Distribution

Journal of the American Statistical Association, 1960
Abstract Values of p (times 10,000) satisfying the equation α = Σ x r = 0 ( n r ) p r (1 – p) n–r are given to four figures for n = 55(5)100, x = 0(1)n − 1 and α = .005, .010, .025, .050.
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Confidence curves and improved exact confidence intervals for discrete distributions

Canadian Journal of Statistics, 2000
The author describes a method for improving standard “exact” confidence intervals in discrete distributions with respect to size while retaining correct level. The binomial, negative binomial, hypergeometric, and Poisson distributions are considered explicitly.
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Confidence and Tolerance Intervals for the Normal Distribution

Journal of the American Statistical Association, 1953
Abstract Confidence and tolerance intervals for the normal distribution are presented for the various cases of known and unknown mean and standard deviation. Practical illustration and interpretation of these intervals are given. Tables are presented permitting a comparison among the intervals.
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