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King, A.J. & Rockafellar, R.T. (1990). Asymptotic Theory for Solutions in Generalized M-Estimation and Stochastic Programming. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-90-076
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Abstract
New techniques of local sensitivity analysis in nonsmooth optimization are applied to the problem of studying the asymptotic behavior (generally non-normal) for solutions in stochastic optimization, and generalized M-estimation -- a reformulation of the traditional maximum-likelihood problem that allows the introduction of hard constraints.
| Item Type: | Monograph (IIASA Working Paper) |
|---|---|
| Research Programs: | Adaption and Optimization (ADO) |
| Depositing User: | IIASA Import |
| Date Deposited: | 15 Jan 2016 02:00 |
| Last Modified: | 27 Aug 2021 17:13 |
| URI: | https://pure.iiasa.ac.at/3379 |
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