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Isotonic median regression for orders representable by rooted trees

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  • Nilotpal Chakravarti

Abstract

The isotonic median regression problem arising in statistics is as follows. We are given m observations falling into n sets, the ith set containing mi observations. The problem requires the determination of n real numbers, the ith being the value “fitted” to each observation in the ith set. These n numbers chosen must satisfy certain (total or partial) order requirements and minimize the distance between the vectors of observed and fitted values in the l1 norm. We present a simple algorithm, of time complexity O(mn), for calculating isotonic median regression for orders representable by rooted trees. We believe that this algorithm is the best currently available for this problem. The algorithm is validated by a linear programming approach which provides additional insight.

Suggested Citation

  • Nilotpal Chakravarti, 1992. "Isotonic median regression for orders representable by rooted trees," Naval Research Logistics (NRL), John Wiley & Sons, vol. 39(5), pages 599-611, August.
  • Handle: RePEc:wly:navres:v:39:y:1992:i:5:p:599-611
    DOI: 10.1002/1520-6750(199208)39:53.0.CO;2-#
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    1. Menendez, J. A. & Salvador, B., 1987. "An algorithm for isotonic median regression," Computational Statistics & Data Analysis, Elsevier, vol. 5(4), pages 399-406, September.
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    4. Nilotpal Chakravarti, 1989. "Isotonic Median Regression: A Linear Programming Approach," Mathematics of Operations Research, INFORMS, vol. 14(2), pages 303-308, May.
    5. Robin Roundy, 1986. "A 98%-Effective Lot-Sizing Rule for a Multi-Product, Multi-Stage Production / Inventory System," Mathematics of Operations Research, INFORMS, vol. 11(4), pages 699-727, November.
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