This monograph addresses the problem of "real-time" curve fitting in the presence of noise, from the computational and statistical viewpoints. It examines the problem of nonlinear regression, where observations are made on a time series whose mean-value function is known except for a vector parameter. In contrast to the traditional formulation, data are imagined to arrive in temporal succession. The.
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Arthur E. Albert, Leland A. Gardner Jr. Stochastic Approximation and NonLinear Regression (MIT Press Classics) free
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