Interval estimation of the critical value in a general linear model |
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Authors: | Y L Tong |
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Institution: | (1) Georgia Institute of Technology, Georgia, USA |
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Abstract: | Summary This paper concerns interval estimation of the critical value θ which satisfies
under the general linear model,Y
i
=μ(x
i
)+ε
i
(i=1,2,···), where
for
and the functional forms off
j
′
s are known. From an asymptotic expansion it is shown that, under reasonable conditions, the limiting distribution of
is normal. Thus in the large-sample case a confidence interval for θ can be obtained. Such a result is useful when one is
interested in carrying out a retrospective analysis rather than designing the experiment (as in the Kiefer-Wolfowitz procedure).
In Section 3 a sequential procedure is considered for confidence intervals with fixed width 2d. It is shown that, for a given stopping variableN,
is also asymptotically normal asd→0. Thus the coverage probability converges to 1−α (preassigned) asd→0. An example of application in estimating the phase parameter in circadian rhythms is given for the purpose of illustration.
Research partially supported by the NSF Grant DMS-8502346. |
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Keywords: | Critical value confidence interval sequential estimation |
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