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Diagnostic Checking in a Flexible Nonlinear Time Series Model
Author(s) -
MEDEIROS MARCELO C.,
VEIGA ALVARO
Publication year - 2003
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/1467-9892.00316
Subject(s) - autoregressive model , mathematics , lagrange multiplier , series (stratigraphy) , nonlinear system , monte carlo method , variance (accounting) , star model , independence (probability theory) , generalization , sample size determination , setar , time series , statistics , autoregressive integrated moving average , mathematical optimization , mathematical analysis , paleontology , physics , accounting , quantum mechanics , business , biology
This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the smooth transition autoregressive (STAR) and the autoregressive artificial neural network (AR‐ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and of constant variance of the error term against the hypothesis that the variance changes smoothly between regimes. The small sample behaviour of the proposed tests is evaluated by a Monte‐Carlo study and the results show that the tests have size close to the nominal one and a good power.