Finding a precise estimate for the smoothness parameter of LSTAR models is notoriously difficult. This paper introduces a robust estimation method for the transition and autoregressive parameters of STAR models, comprising gradient descent and singular value decomposition to account for heteroscedastic noise.
A Robust algorithm for parameter estimation in Smooth Transition Autoregressive models
BEKIROS S
2009-01-01
Abstract
Finding a precise estimate for the smoothness parameter of LSTAR models is notoriously difficult. This paper introduces a robust estimation method for the transition and autoregressive parameters of STAR models, comprising gradient descent and singular value decomposition to account for heteroscedastic noise.
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