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Confidence Intervals

Annals of Internal Medicine, 1986
W S, Browner, T B, Newman
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Bootstrap Confidence Intervals

2010
In statistical analysis of climate time series, our aim (Chapter 1) is to estimate parameters of X trend(T), X out(T), S(T) and X noise(T). Denote in general such a parameter as θ. An estimator, \( \hat{\theta } \), is a recipe how to calculate θ from a set of data. The data, discretely sampled time series \( \{t\left( i \right),x\left( i \right)\}_{{i=
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Fuzzy confidence intervals

Fuzzy Sets and Systems, 1983
Fuzzy numbers have heretofore been conceived simply as convex fuzzy subsets of the real line, especially in the context of possibility theory. This paper proposes an alternative interpretation of fuzzy numbers: fuzzy confidence intervals. This number concept is particularly appropriate to problems of optimization with a fuzzy objective function or ...
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Simultaneous confidence intervals

Scandinavian Actuarial Journal, 1966
Abstract Let x = (x 1 ..., x n)′ be an n-dimensional normally distributed stochastic vector with mean m = (m 1 ..., m n)′ belonging to a subspace M of Rn and with covariance matrix C. It is well known how to obtain simultaneous confidence intervals for a class of linear functionals of the mean in different contexts.
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Generalized Confidence Intervals

Journal of the American Statistical Association, 1993
Abstract The definition of a confidence interval is generalized so that problems such as constructing exact confidence regions for the difference in two normal means can be tackled without the assumption of equal variances. Under certain conditions, the extended definition is shown to preserve a repeated sampling property that a practitioner expects ...
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Confidence in confidence intervals

JBI Database of Systematic Reviews and Implementation Reports, 2016
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