Convergence Of Repetitive Guesstimation Algorithm On A Linear Regression Problem
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.
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Volume (Year): (2001)
Issue (Month): 2 (June)
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