Search Results - subject:"Stochastic Approximation"

Parameter estimation in general state-space models using particle methods

Doucet, Arnaud; Tadić, Vladislav - In: Annals of the Institute of Statistical Mathematics 55 (2003) 2, pp. 409-422

Persistent link: https://www.econbiz.de/10005616283

How to apply the Score-Function method to standard discrete event simulation tools in order to optimise a set of system parameters simultaneously: A Job-Shop example will be discussed.

Nielsen, Erland Hejn - Institut for Marketing og Organisation, Aarhus Universitet - 2000

Persistent link: https://www.econbiz.de/10005802240

Revenue Management Without Forecasting or Optimization: An Adaptive Algorithm for Determining Airline Seat Protection Levels

Ryzin, Garrett van; McGill, Jeff - In: Management Science 46 (2000) 6, pp. 760-775

adjustments of the seat protection levels in accordance with the optimality conditions of Brumelle and McGill (1993). Stochastic … approximation theory is used to prove the convergence of this adaptive algorithm to the optimal protection levels. In a simulation …

Persistent link: https://www.econbiz.de/10009208568

Chapter 7 Learning dynamics

Evans, George W.; Honkapohja, Seppo - In: Handbook of macroeconomics : volume 1, part A, (pp. 449-542). 1999

under learning as a SRA (stochastic recursive algorithm) and to analyze convergence by the method of stochastic … approximation based on an associated differential equation. Global stability, local stability and instability results for SRAs are …

Persistent link: https://www.econbiz.de/10014024243

Asymptotic Expansions for the Stochastic Approximation Averaging Procedure in Continuous Time

Pergamenshchikov, S. - In: Statistical Inference for Stochastic Processes 1 (1998) 2, pp. 197-223

Persistent link: https://www.econbiz.de/10005184596

Solving stochastic structural optimization problems by RSM-based stochastic approximation methods — gradient estimation in case of intermediate variables

Marti, Kurt - In: Computational Statistics 46 (1997) 3, pp. 409-434

expectation operator andD is a given closed, convex subset of ℛ r . Stochastic approximation methods are considered for solving (1 …

Persistent link: https://www.econbiz.de/10010847960

Solving stochastic structural optimization problems by RSM-based stochastic approximation methods — gradient estimation in case of intermediate variables

Marti, Kurt - In: Mathematical Methods of Operations Research 46 (1997) 3, pp. 409-434

andD is a given closed, convex subset of ℛ<Superscript> r </Superscript>. Stochastic approximation methods are considered …

Persistent link: https://www.econbiz.de/10010999966

On a stochastic approximation procedure based on averaging

Schwabe, Rainer; Walk, Harro - In: Metrika 44 (1996) 1, pp. 165-180

Persistent link: https://www.econbiz.de/10005756384

Optimization of the Transient and Steady-State Behavior of Discrete Event Systems

Andradóttir, Sigrún - In: Management Science 42 (1996) 5, pp. 717-737

measure of interest and its gradient, and we present conditions that guarantee that the Robbins-Monro stochastic approximation …

Persistent link: https://www.econbiz.de/10009191300

Stochastic Optimization by Simulation: Convergence Proofs for the GI/G/1 Queue in Steady-State

L'Ecuyer, Pierre; Glynn, Peter W. - In: Management Science 40 (1994) 11, pp. 1562-1578

stochastic approximation algorithms, to perform so-called "single-run optimizations" of steady-state systems. Under mild …

Persistent link: https://www.econbiz.de/10009197436