An investigation of lag identification tools for vector nonlinear time series

Exploratory methods for determining appropriate lagged vsrlables in a vector nonlinear time series model are investigated. The first is a multivariate extension of the R statistic considered by Granger and Lin (1994), which is based on an estimate of the mutual information criterion. The second meth...

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Bibliographic Details
Published in:	Communications in statistics. Theory and methods Vol. 29; no. 8; pp. 1677 - 1701
Main Authors:	Harvill, Janc L., Ray, Bonnic K.
Format:	Journal Article
Language:	English
Published:	Philadelphia, PA Marcel Dekker, Inc 01-01-2000 Taylor & Francis
Subjects:	Exact sciences and technology Inference from stochastic processes; time series analysis Kendall's ρ Mathematics Mutual information criterion Probability and statistics Sciences and techniques of general use Statistics Independence test Statistical estimation Statistical simulation Mutual information fonction Non linear model Time series
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Summary:	Exploratory methods for determining appropriate lagged vsrlables in a vector nonlinear time series model are investigated. The first is a multivariate extension of the R statistic considered by Granger and Lin (1994), which is based on an estimate of the mutual information criterion. The second method uses Kendall's ρ and partial ρ statistics for lag determination. The methods provide nonlinear analogues of the autocorrelation and partial autocorrelation matrices for a vector time series. Simulation studies indicate that the R statistic reliabiy identifies appropriate lagged nonlinear moving average terms in a vector time series, while Kendall's ρ and partial ρ statistics have some power in identifying appropirate lagged nonlinear moving average and autoregressive terms, respectively, when the nonlinear relationship between lagged variables is monotonic. For illustration, the methods are applied to set of annual temperature and tree ring measurements at Campito Mountain In California.
ISSN:	0361-0926 1532-415X
DOI:	10.1080/03610920008832573