The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Detecting Outliers in Deterministic Nonparametric Frontier Models With Multiple Outputs
Abstract
This article provides a statistical methodology for identifying outliers in production data with multiple inputs and outputs used in deterministic nonparametric frontier models. The methodology is useful in identifying observations that may contain some form of measurement error and thus merit closer scrutiny. When data checking is costly, the methodology may be used to rank observations in terms of their dissimilarity to other observations in the data, suggesting a priority for further inspection of the data.
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Cites
Regression Diagnostics: Identifying Influential Data and Sources of Collinearity
Belsley, D. A., Kuh, E., & Welsch, R. E. (1980) · Wiley Series in Probability and Statistics · doi:10.1002/0471725153 · Cited by 7,297
Production Frontiers and Productive Efficiency
Lovell, C. A. K. (1993) · The Measurement of Productive Efficiency · doi:10.1093/oso/9780195072181.003.0001 · Cited by 687
Cited by
Estimation and Inference in Nonparametric Frontier Models: Recent Developments and Perspectives
Simar, L., & Wilson, P. W. (2013) · Foundations and Trends in Econometrics · doi:10.1561/0800000020 · Cited by 382
Self-citationDrinking water and sanitation: progress in 73 countries in relation to socioeconomic indicators
Luh, J., & Bartram, J. (2016) · Bulletin of the World Health Organization · doi:10.2471/blt.15.162974 · Cited by 32
Metadata
- Authors
- Wilson, P. W.
- Venue
- Journal of Business & Economic Statistics
- Publisher
- Informa UK Limited
- Published
- 1993-07
- Volume
- 11
- Issue
- 3
- Pages
- 319-323
- ISSN
- 0735-0015 (ISSN-L)
- 1537-2707
- OpenAlex
- W2031931895
- Cited by
- 345
- References
- 2
- FWCI
- 4.13
- Type
- journal article
- Language
- en
- Open access
- closed
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