CONVERGENCE OF REPETITIVE GUESSTIMATION ALGORITHM ON A LINEAR REGRESSION PROBLEM
Adriana Agapie ()
Journal for Economic Forecasting, 2001, issue 2, 118-126
Repetitive Stochastic Guesstimation (RSG) is a probabilistic algorithm introduced in Charemza (1996) which mimics the usual guessing of the parameters involved in a complex large macroeconomic model. The paper analyzes the objective function employed by RSG and it establishes sufficient conditions on the RSG components in order to achieve global convergence for a specific task, namely the linear regression problem.
Keywords: estimation; macromodels; computational techniques; methodology (search for similar items in EconPapers)
JEL-codes: C6 C63 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:rjr:romjef:v::y:2001:i:2:p:118-126
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