@techreport{Winker2005convergence,
abstract = {The convergence of estimators, e.g. maximum likelihood estimators, for
increasing sample size is well understood in many cases. However, even
when the rate of convergence of the estimator is known, practical application
is hampered by the fact, that the estimator cannot always be obtained at
tenable computational cost.
This paper combines the analysis of convergence of the estimator itself
with the analysis of the convergence of stochastic optimization algorithms,
e.g. threshold accepting, to the theoretical estimator. We discuss the joint
convergence of estimator and algorithm in a formal framework.
An application to a GARCH-model demonstrates the approach in practice
by estimating actual rates of convergence through a large scale simulation
study. Despite of the additional stochastic component introduced by the
use of an optimization heuristic, the overall quality of the estimates turns out
to be superior compared to conventional approaches.},
author = {Peter Winker and Dietmar Maringer},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {C63; C22; 330; GARCH; Threshold Accepting; Optimization Heuristics; Convergence; Sch\"{a}tztheorie; ARCH-Modell; Theorie},
language = {eng},
number = {2005,004E},
title = {The convergence of optimization based estimators : theory and application to a GARCH-model},
type = {Discussion paper / Universit\"{a}t Erfurt, Staatswissenschaftliche Fakult\"{a}t},
url = {http://hdl.handle.net/10419/23941},
year = {2005}
}
