全球智库信息集成服务系统(G2TT): Asymptotic Theory for Solutions in Generalized M-Estimation and Stochastic Programming.

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来源类型	Monograph (IIASA Working Paper)
规范类型	论文
	Asymptotic Theory for Solutions in Generalized M-Estimation and Stochastic Programming.
	King AJ; Rockafellar RT
发表日期	1990
出版者	IIASA, Laxenburg, Austria: WP-90-076
出版年	1990
语种	英语
摘要	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.
主题	Adaption and Optimization (ADO)
URL	http://pure.iiasa.ac.at/id/eprint/3379/
来源智库	International Institute for Applied Systems Analysis (Austria)
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/123802
推荐引用方式 GB/T 7714	King AJ,Rockafellar RT. Asymptotic Theory for Solutions in Generalized M-Estimation and Stochastic Programming.. 1990.