Results 241 to 250 of about 462,419 (289)

Successive generalized confidence intervals

2022
The majority of work on multiple comparisons is on comparing the means of k ⩾3 populations following the work of Tukey (1953) on pairwise comparisons of k population means, of Dunnett (1955) on comparisons of several means with a control mean, and of Scheff ́e (1953) on all-contrast comparisons among the population means.
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Simultaneous Confidence Intervals for the General Linear Model

Biometrics, 1987
This paper describes, compares, and illustrates four known simultaneous confidence interval procedures for the general linear model. It is shown that three of the four procedures can be ordered by the increasing length of their confidence intervals as follows: (i) Šidák multivariate t- distribution intervals, (ii) Šidák independent t-distribution ...
Fuchs, Camil, Sampson, Allan R.
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Generalized confidence intervals for process capability indices

Quality and Reliability Engineering International, 2006
AbstractThe concept of generalized confidence intervals is used to derive lower confidence limits for some of the commonly used process capability indices. For the cases where approximate lower confidence limits are already available, numerical comparisons are made among the available approximations and the generalized lower confidence limit.
Thomas Mathew, G. Sebastian, K. M. Kurian   +2 more
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Efficiency of Confidence Intervals Generated by Repeated Subsample Calculations

Biometrika, 1970
Summary: Confidence intervals for a mean may be obtained from n observations continuously and symmetrically distributed about the mean, by computing the means of all \(2^n-1\) subsets, or subsamples, of the observations. The true mean lies in each of the intervals between the ordered subsample means with probability \(2^{-n}\). In order to reduce the \(
Forsythe, Alan, Hartigan, J. A.
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Confidence Intervals of Variance Functions in Generalized Linear Model

Acta Mathematicae Applicatae Sinica, English Series, 2006
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Zhou, Yong, Li, Daoji
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Generalization of distribution – Free confidence intervals for bioavailability ratios

European Journal of Clinical Pharmacology, 1985
The confidence interval approach to bioavailability assessment depends first on selection of the confidence level, usually 95%, and then determination of the confidence limits for the expected bioavailability ratio AUC(Test)/AUC(Reference).
V W, Steinijans, E, Diletti
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Confidence intervals for for the generalized exponential distribution

Statistical Methodology, 2012
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Hajebi, Mahtab, Rezaei, Sadegh, Nadarajah, Saralees   +2 more
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Generating confidence intervals via model comparison

2004
Abstract In this chapter, we’ll develop a third method to obtain the confidence interval of a best-fit parameter (to complement the asymptotic and Monte Carlo methods described in the previous two chapters). It is based on the method to be discussed below in Chapter 22.
Harvey Motulsky, Arthur Christopoulos
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Sequential confidence intervals based on generalized m-statistics

Sequential Analysis, 1987
A broad class of statistics including U-statistics and generalized quantiles (U- quantiles) can be viewed as solutions to an equation of the form . For these generalized M- estimators we develop weak and strong representations. As an application of the weak representation we show a central limit theorem for Mn. From the a.s.
M. Aerts, P. Janssen, N. Veraverbeke
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Generating confidence intervals by Monte Carlo simulations

2004
Abstract As discussed in the previous chapter, the asymptotic method built in to most nonlinear regression programs is only an approximate method to determine the confidence interval of a best-fit parameter. This chapter presents one alternative method, and the next chapter presents still another alternative method.
Harvey Motulsky, Arthur Christopoulos
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