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An Algorithm for Restricted Least Squares Regression
Abstract
A commonly occurring problem in statistics is that of minimizing a least squares expression subject to side constraints. Here a simple iterative algorithm is presented and shown to converge to the desired solution. Several examples are presented, including finding the closest concave (convex) function to a set of points and other general quadratic programming problems. The dual problem to the basic problem is also discussed and a solution for it is given in terms of the algorithm. Finally, extensions to expressions other than least squares are given.
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Cites
The Isotonic Regression Problem and its Dual
Barlow, R. E., & Brunk, H. D. (1972) · Journal of the American Statistical Association · doi:10.1080/01621459.1972.10481216 · Cited by 245
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Metadata
- Authors
- Dykstra, R. L.
- Venue
- Journal of the American Statistical Association
- Publisher
- Informa UK Limited
- Published
- 1983-12
- Volume
- 78
- Issue
- 384
- Pages
- 837-842
- ISSN
- 0162-1459 (ISSN-L)
- 1537-274X
- OpenAlex
- W2050958540
- Cited by
- 551
- References
- 1
- FWCI
- 4.11
- Type
- journal article
- Language
- en
- Open access
- closed
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