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TitleModelling time series when mean and variability both change
Publication TypeJournal Article
Year of Publication2008
AuthorsWithers, C.S., Krouse D.P., Pearson C.P., and Nadarajah S.
JournalMathematics and Computers in Simulation
Volume77
Issue1
Pagination57 - 63
Date Published2008
ISSN03784754 (ISSN)
KeywordsChanging variability, Error analysis, Least squares approximations, Likelihood ratio test, MATHEMATICAL MODELS, Non-stationary series, Nonlinear analysis, Parameter estimation, Polynomials, time series analysis, Trends
AbstractAn extended least-squares method is described which allows us to model the location and scale of a process parametrically without specifying any parametric form for the distribution of the errors. The degree of the associated polynomials is chosen using a step-down method on a table of p-values. A pseudo-likelihood ratio test is given. The concepts of upper and lower return levels are extended to non-stationary series. The method is applied to annual means and extremes of Auckland temperatures. Evidence is found that the mean is changing non-linearly and the variance is also changing for all three series. © 2007 IMACS.
URLhttp://www.scopus.com/inward/record.url?eid=2-s2.0-38649130614&partnerID=40&md5=d72b4cb7d3dcbf1819fd82da79e99d9d
DOI10.1016/j.matcom.2007.01.039

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