The DOI matches its Crossref record.
Theory of Point Estimation
Abstract
Preface to the Second Edition.- Preface to the First Edition.- List of Tables.- List of Figures.- List of Examples.- Table of Notation.- Preparations.- Unbiasedness.- Equivariance.- Average Risk Optimality.- Minimaxity and Admissibility.- Asymptotic Optimality.- References.- Author Index.- Subject Index.
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Citations
Cited by
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Zou, H. (2006) · Journal of the American Statistical Association · doi:10.1198/016214506000000735 · Cited by 7,470
Strictly Proper Scoring Rules, Prediction, and Estimation
Gneiting, T., & Raftery, A. E. (2007) · Journal of the American Statistical Association · doi:10.1198/016214506000001437 · Cited by 5,793
Colwell, R. K., Chao, A., Gotelli, N. J., Lin, S.-Y., Mao, C. X., Chazdon, R. L., & Longino, J. T. (2012) · Journal of Plant Ecology · doi:10.1093/jpe/rtr044 · Cited by 1,921
Bias and Efficiency of Meta-Analytic Variance Estimators in the Random-Effects Model
Viechtbauer, W. (2005) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986030003261 · Cited by 1,699
Raue, A., Kreutz, C., Maiwald, T., Bachmann, J., Schilling, M., Klingmüller, U., & Timmer, J. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp358 · Cited by 1,442
Metadata
- Authors
- Ziegel, E. R., Lehmann, E. L., & Casella, G.
- Venue
- Technometrics
- Publisher
- JSTOR
- Published
- 1999-08
- Volume
- 41
- Issue
- 3
- Pages
- 274
- ISSN
- 0040-1706 (ISSN-L)
- OpenAlex
- W2122759946
- Cited by
- 4,203
- References
- 0
- FWCI
- 160.70
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Theory of Point Estimation. https://app.cochat.ai/papers/10.2307/1270597
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- Ziegel, E. R., Lehmann, E. L., & Casella, G. (1999). Theory of Point Estimation. Technometrics. https://doi.org/10.2307/1270597
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
