DocumentCode
942911
Title
Confidence intervals based on one or more observations
Author
Blachman, Nelson M. ; Machol, Robert E.
Volume
33
Issue
3
fYear
1987
fDate
5/1/1987 12:00:00 AM
Firstpage
373
Lastpage
382
Abstract
On the basis of
observations, confidence limits of the form
are constructed for the location (e.g., the median) of any distribution of known form with unknown location and dispersion (scale), where
and
are the sample mean and "unbiased" standard deviation. Particular attention is given to the values of
needed for the Cauchy and uniform distributions. The latter
suffices for any (unknown) symmetric unimodal distribution if
. A table compares these values of
for
, and
with those for the normal case, which are derived here very simply and are identical with those found by "Student." We are also able to include the case of a single observation
, where confidence intervals of various forms are made just wide enough for the least favorable dispersion. They, therefore, include the true location with at least but, in general, not exactly the desired probability; these intervals involve a predetermined value that plays a role reminiscent of but quite different from that of the prior distribution that would enter into a Bayesian analysis. In addition, upper confidence limits for the dispersion are constructed for
.
observations, confidence limits of the form
are constructed for the location (e.g., the median) of any distribution of known form with unknown location and dispersion (scale), where
and
are the sample mean and "unbiased" standard deviation. Particular attention is given to the values of
needed for the Cauchy and uniform distributions. The latter
suffices for any (unknown) symmetric unimodal distribution if
. A table compares these values of
for
, and
with those for the normal case, which are derived here very simply and are identical with those found by "Student." We are also able to include the case of a single observation
, where confidence intervals of various forms are made just wide enough for the least favorable dispersion. They, therefore, include the true location with at least but, in general, not exactly the desired probability; these intervals involve a predetermined value that plays a role reminiscent of but quite different from that of the prior distribution that would enter into a Bayesian analysis. In addition, upper confidence limits for the dispersion are constructed for
.Keywords
Estimation; Statistics; Bayesian methods; Cities and towns; Density functional theory; FAA; Government; Helium; Information theory; Laboratories; Meetings; Statistical distributions;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1987.1057306
Filename
1057306
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