Constrained estimation and the theorem of Kuhn-Tucker

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Constrained estimation and the theorem of Kuhn-Tucker

There are many statistical problems in which the parameter of interest is restricted to a subset of the parameter space. The constraint(s) may reflect prior knowledge about the value of the parameter, or, may be a device used to improve the statistical properties of the estimator. Estimation and inferential procedures for such models may be derived using the theorem of Kuhn-Tucker (KT). The the...

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Duality and the “ convex ” Karush - Kuhn - Tucker theorem ∗ Erik

Our approach to the Karush-Kuhn-Tucker theorem in [OSC] was entirely based on subdifferential calculus (essentially, it was an outgrowth of the two subdifferential calculus rules contained in the Fenchel-Moreau and Dubovitskii-Milyutin theorems, i.e., Theorems 2.9 and 2.17 of [OSC]). On the other hand, Proposition B.4(v) in [OSC] gives an intimate connection between the subdifferential of a fun...

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Working with the “ convex ” Karush - Kuhn - Tucker theorem ∗

1 The " convex " KKT theorem: a recapitulation We recall the Karush-Kuhn-Tucker theorem for convex programming, as treated in the previous lecture (see Corollary 3.5 of [OSC]).

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The Kuhn-Tucker and envelope theorems can be used to characterize the solution to a wide range of constrained optimization problems: static or dynamic, under perfect foresight or featuring randomness and uncertainty. In addition, these same two results provide foundations for the work on the maximum principle and dynamic programming that we will do later on. For both of these reasons, the Kuhn-...

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In this note, we revisit the classical first order necessary condition in mathematical programming in infinite dimension. The constraint set being defined by C = g−1(K) where g is a smooth map between Banach spaces, and K a closed convex cone, we show that existence of Lagrange-Karush-Kuhn-Tucker multipliers is equivalent to metric subregularity of the multifunction defining the constraint, and...

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ژورنال

عنوان ژورنال: Journal of Applied Mathematics and Decision Sciences

سال: 2006

ISSN: 1173-9126,1532-7612

DOI: 10.1155/jamds/2006/92970