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The asymptotic distribution of the likelihood ratio for autoregressive time series with a regression trend

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Author Info
Swensen, Anders Rygh
Abstract

It is shown that the likelihood ratio of an autoregressive time series of finite order with a regression trend is asymptotically normal. This result is used to derive the power of a test for positive correlation of the residuals under local autoregressive alternatives. The test is based on the Durbin-Watson statistics.

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Article provided by Elsevier in its journal Journal of Multivariate Analysis.

Volume (Year): 16 (1985)
Issue (Month): 1 (February)
Pages: 54-70
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Handle: RePEc:eee:jmvana:v:16:y:1985:i:1:p:54-70

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Keywords: Regression autoregressive errors local asymptotic normality test for dependence;

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  1. Marc Hallin & Abdeslam Serroukh, 1998. "Adaptive Estimation of the Lag of a Long–memory Process," Statistical Inference for Stochastic Processes, Springer, vol. 1(2), pages 111-129, May. [Downloadable!] (restricted)
  2. Oliver Linton & Douglas G. Steigerwald, 1995. "Adaptive Testing in ARCH Models," Cowles Foundation Discussion Papers 1105, Cowles Foundation, Yale University. [Downloadable!]
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