POWER OF THE NEURAL NETWORK LINEARITY TEST
作者： Timo Teräsvirta , Chien-Fu Lin , Clive W. J. Granger
DOI: 10.1111/J.1467-9892.1993.TB00139.X
关键词:
摘要: Abstract. Recently, a new linearity test for time series was introduced based on concepts from the theory of neural networks. Lee et al. have already studied power properties this and they are further investigated here. They compared by simulation with those Lagrange multiplier (LM) type that we derive same single-hidden-layer network model. The auxiliary regression our LM is simple cubic ‘dual’ Volterra expansion original series, appears superior overall to other test.
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