Open Access
September, 1982 An Algorithm for Isotonic Regression for Two or More Independent Variables
Richard L. Dykstra, Tim Robertson
Ann. Statist. 10(3): 708-716 (September, 1982). DOI: 10.1214/aos/1176345866


Algorithms for solving the isotonic regression problem in more than one dimension are difficult to implement because of the large number of lower sets present or because they involve search techniques which require a significant amount of checking and readjustment. Here a new algorithm for solving this problem based on a simple iterative technique is proposed and shown to converge to the correct solution.


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Richard L. Dykstra. Tim Robertson. "An Algorithm for Isotonic Regression for Two or More Independent Variables." Ann. Statist. 10 (3) 708 - 716, September, 1982.


Published: September, 1982
First available in Project Euclid: 12 April 2007

zbMATH: 0485.65099
MathSciNet: MR663427
Digital Object Identifier: 10.1214/aos/1176345866

Primary: 65D15
Secondary: 49D05

Keywords: convex cones , dual convex cones , isotone regression , minimal lower sets algorithm , projections

Rights: Copyright © 1982 Institute of Mathematical Statistics

Vol.10 • No. 3 • September, 1982
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