Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1140958 | Mathematics and Computers in Simulation | 2008 | 7 Pages |
Abstract
An 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.
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Authors
C.S. Withers, D.P. Krouse, C.P. Pearson, S. Nadarajah,