A mixed-type test for linearity in time series

Hong Zhi An, Li Xing Zhu, Runze Li

Research output: Contribution to journalArticle

4 Citations (Scopus)

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
StatePublished - Aug 1 2000

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Linearity
Time series
Statistics
Statistic
Curse of Dimensionality
Time Series Models
Autoregressive Model
Goodness of fit
Linear Model
Series
Alternatives
Simulation

All Science Journal Classification (ASJC) codes

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

Cite this

An, Hong Zhi ; Zhu, Li Xing ; Li, Runze. / A mixed-type test for linearity in time series. In: Journal of Statistical Planning and Inference. 2000 ; Vol. 88, No. 2. pp. 339-353.
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A mixed-type test for linearity in time series. / An, Hong Zhi; Zhu, Li Xing; Li, Runze.

In: Journal of Statistical Planning and Inference, Vol. 88, No. 2, 01.08.2000, p. 339-353.

Research output: Contribution to journalArticle

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