The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Bayesian Estimation and Prediction Using Asymmetric Loss Functions
Abstract
Estimators and predictors that are optimal relative to Varian's asymmetric LINEX loss function are derived for a number of well-known models. Their risk functions and Bayes risks are derived and compared with those of usual estimators and predictors. It is shown that some usual estimators, for example, a scalar sample mean or a scalar least squares regression coefficient estimator, are inadmissible relative to asymmetric LINEX loss by providing alternative estimators that dominate them uniformly in terms of risk.
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Cites
Mathematical Statistics A Decision Theoretic Approach
Rogers, G. S. (1968) · Technometrics · doi:10.1080/00401706.1968.10490555 · Cited by 1,488
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Confidence Sets for the Mean of a Multivariate Normal Distribution
Stein, C. (1962) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1962.tb00458.x · Cited by 247
STATISTICAL DECISION THEORY: FOUNDATIONS, CONCEPTS, AND METHODS
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Discussion on Professor Stein’s Paper
(1962) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.2517-6161.1962.tb00459.x · Cited by 77
Cited by
Chapter 4 Forecast Combinations
Timmermann, A. (2006) · Handbook of Economic Forecasting · doi:10.1016/s1574-0706(05)01004-9 · Cited by 1,314
A Survey of Predictive Modeling on Imbalanced Domains
Branco, P., Torgo, L., & Ribeiro, R. P. (2017) · ACM Computing Surveys · doi:10.1145/2907070 · Cited by 1,129
Kumar, R., & Goyal, R. (2020) · Computers & Security · doi:10.1016/j.cose.2020.101967 · Cited by 97
Metadata
- Authors
- Zellner, A.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1986-06
- Volume
- 81
- Issue
- 394
- Pages
- 446-451
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2061885628
- Cited by
- 913
- References
- 6
- FWCI
- 8.43
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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