A decision-theoretic approach to interval estimation
Publication
, Journal Article
Winkler, RL
Published in: Journal of the American Statistical Association
January 1, 1972
Under an appropriate loss function, interval estimation may be regarded as a Bayesian decision-making procedure in which the objective is to find an interval that minimizes expected loss. For various loss functions, the behavior of the optimal interval is investigated, a comparison is made with the usual non-decision-theoretic interval estimates, and applications and examples are discussed. © Taylor & Francis Group, LLC.
Duke Scholars
Published In
Journal of the American Statistical Association
DOI
EISSN
1537-274X
ISSN
0162-1459
Publication Date
January 1, 1972
Volume
67
Issue
337
Start / End Page
187 / 191
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1603 Demography
- 1403 Econometrics
- 0104 Statistics
Citation
APA
Chicago
ICMJE
MLA
NLM
Winkler, R. L. (1972). A decision-theoretic approach to interval estimation. Journal of the American Statistical Association, 67(337), 187–191. https://doi.org/10.1080/01621459.1972.10481224
Winkler, R. L. “A decision-theoretic approach to interval estimation.” Journal of the American Statistical Association 67, no. 337 (January 1, 1972): 187–91. https://doi.org/10.1080/01621459.1972.10481224.
Winkler RL. A decision-theoretic approach to interval estimation. Journal of the American Statistical Association. 1972 Jan 1;67(337):187–91.
Winkler, R. L. “A decision-theoretic approach to interval estimation.” Journal of the American Statistical Association, vol. 67, no. 337, Jan. 1972, pp. 187–91. Scopus, doi:10.1080/01621459.1972.10481224.
Winkler RL. A decision-theoretic approach to interval estimation. Journal of the American Statistical Association. 1972 Jan 1;67(337):187–191.
Published In
Journal of the American Statistical Association
DOI
EISSN
1537-274X
ISSN
0162-1459
Publication Date
January 1, 1972
Volume
67
Issue
337
Start / End Page
187 / 191
Related Subject Headings
- Statistics & Probability
- 4905 Statistics
- 3802 Econometrics
- 1603 Demography
- 1403 Econometrics
- 0104 Statistics