Admissibility of Confidence Estimators in the Regression Model

In the regression model, we assume that the independent variables are random instead of fixed. Consider the problem of estimating the coverage function of a usual confidence interval for the unknown intercept parameter. In this paper, we consider a case in which the number of unknown parameters is s...

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Veröffentlicht in:Journal of multivariate analysis Jg. 76; H. 2; S. 267 - 276
1. Verfasser: Wang, Hsiuying
Format: Journal Article
Sprache:Englisch
Veröffentlicht: San Diego, CA Elsevier Inc 01.02.2001
Elsevier
Schriftenreihe:Journal of Multivariate Analysis
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ISSN:0047-259X, 1095-7243
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Abstract In the regression model, we assume that the independent variables are random instead of fixed. Consider the problem of estimating the coverage function of a usual confidence interval for the unknown intercept parameter. In this paper, we consider a case in which the number of unknown parameters is smaller than 5. We show that the usual constant coverage probability estimator is admissible in the usual sense in this case. Note that this estimator is inadmissible in the usual sense in the other case where the number of unknown parameters is greater than 4.
AbstractList In the regression model, we assume that the independent variables are random instead of fixed. Consider the problem of estimating the coverage function of a usual confidence interval for the unknown intercept parameter. In this paper, we consider a case in which the number of unknown parameters is smaller than 5. We show that the usual constant coverage probability estimator is admissible in the usual sense in this case. Note that this estimator is inadmissible in the usual sense in the other case where the number of unknown parameters is greater than 4.
Author Wang, Hsiuying
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10.1214/aos/1176347602
10.1214/aos/1018031210
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Issue 2
Keywords confidence interval, admissibility, coverage function, the usual coverage probability estimator, ancillary statistic
Admissibility
Parameter estimation
Admissible estimator
Statistical theory
Confidence limit
Non parametric estimation
Tolerance limit
Statistical estimation
Statistical decision
Independent variable
Confidence interval
Statistical regression
Regression model
Decision theory
Bayes decision
Random variable
Language English
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References Wang (RF4) 1998; 36
Brown (RF1) 1990; 18
Wang (RF3) 1999; 27
Brown, Gene Hwang (RF2) 1990
Brown (10.1006/jmva.2000.1912_RF1) 1990; 18
Wang (10.1006/jmva.2000.1912_RF3) 1999; 27
Wang (10.1006/jmva.2000.1912_RF4) 1998; 36
Brown (10.1006/jmva.2000.1912_RF2) 1990
References_xml – volume: 27
  start-page: 610
  year: 1999
  end-page: 626
  ident: RF3
  article-title: Brown's paradox in the estimated confidence approach
  publication-title: Ann. Statist.
– year: 1990
  ident: RF2
  article-title: Admissibility of confidence estimators
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  ident: RF1
  article-title: An ancillarity paradox which appears in multiple linear regression (with discussion)
  publication-title: Ann. Statist.
– volume: 36
  start-page: 365
  year: 1998
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  ident: RF4
  article-title: Admissibility of the constant coverage probability estimator for estimating the coverage function of certain confidence interval
  publication-title: Statist. Probab. Lett.
– year: 1990
  ident: 10.1006/jmva.2000.1912_RF2
  article-title: Admissibility of confidence estimators
– volume: 36
  start-page: 365
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  ident: 10.1006/jmva.2000.1912_RF4
  article-title: Admissibility of the constant coverage probability estimator for estimating the coverage function of certain confidence interval
  publication-title: Statist. Probab. Lett.
  doi: 10.1016/S0167-7152(97)00083-7
– volume: 18
  start-page: 471
  year: 1990
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  article-title: An ancillarity paradox which appears in multiple linear regression (with discussion)
  publication-title: Ann. Statist.
  doi: 10.1214/aos/1176347602
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  start-page: 610
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  ident: 10.1006/jmva.2000.1912_RF3
  article-title: Brown's paradox in the estimated confidence approach
  publication-title: Ann. Statist.
  doi: 10.1214/aos/1018031210
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SubjectTerms admissibility
ancillary statistic
confidence interval
confidence interval, admissibility, coverage function, the usual coverage probability estimator, ancillary statistic
coverage function
Decision theory
Exact sciences and technology
Mathematics
Nonparametric inference
Parametric inference
Probability and statistics
Sciences and techniques of general use
Statistics
the usual coverage probability estimator
Title Admissibility of Confidence Estimators in the Regression Model
URI https://dx.doi.org/10.1006/jmva.2000.1912
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