A mixed-type test for linearity in time series

Hong Zhi An, Li Xing Zhu, Run Ze Li

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

We propose a new test for linearity of time-series model by introducing a mixed-type statistic. It consists of a Cramer-Von Mises-type statistic and a goodness-of-fit statistic concerned only with fitting a linear autoregressive model. The computation involved in the new test is considerably simple and the curse of dimensionality is partly avoided. It is shown that the test is consistent against all fixed alternatives to linearity in stationary autoregressive series. The simulation results show that the test has good performance of power.

Original languageEnglish (US)
Pages (from-to)339-353
Number of pages15
JournalJournal of Statistical Planning and Inference
Volume88
Issue number2
DOIs
StatePublished - Aug 1 2000

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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