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Polynomial regression under shape constraints

Abstract : Calculating regression under shape constraints is a problem addressed by statisticians since long. This paper shows how to calculate a polynomial regression of any degree and of any number of variables under shape constraints, which include bounds, monotony, concavity constraints. Theoretical explanations are first introduced for monotony constraints and then applied to ad hoc examples to show the behavior of the proposed algorithm. Two real industrial cases are then detailed and worked out.
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https://hal.inria.fr/hal-01073514
Contributor : Francois Wahl <>
Submitted on : Wednesday, March 4, 2015 - 10:23:44 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:57 PM
Long-term archiving on: : Friday, June 5, 2015 - 11:31:19 AM

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  • HAL Id : hal-01073514, version 2

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Francois Wahl, T Espinasse. Polynomial regression under shape constraints. 2014. ⟨hal-01073514v2⟩

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