| Title | Modelling time series when mean and variability both change |
| Publication Type | Journal Article |
| Year of Publication | 2008 |
| Authors | Withers, C.S., Krouse D.P., Pearson C.P., and Nadarajah S. |
| Journal | Mathematics and Computers in Simulation |
| Volume | 77 |
| Issue | 1 |
| Pagination | 57 - 63 |
| Date Published | 2008 |
| ISSN | 03784754 (ISSN) |
| Keywords | Changing variability, Error analysis, Least squares approximations, Likelihood ratio test, MATHEMATICAL MODELS, Non-stationary series, Nonlinear analysis, Parameter estimation, Polynomials, time series analysis, Trends |
| 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. © 2007 IMACS. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-38649130614&partnerID=40&md5=d72b4cb7d3dcbf1819fd82da79e99d9d |
| DOI | 10.1016/j.matcom.2007.01.039 |
