The Effect of the Estimation on Goodness-of-Fit Tests in Time Series Models

Yue Fang (First Author)

科研成果: 期刊稿件期刊论文

摘要

We analyze, by simulation, the finite-sample properties of goodness-of-fit tests based on residual autocorrelation coefficients (simple and partial) obtained using different estimators frequently used in the analysis of autoregressive moving-average time-series models. The estimators considered are unconditional least squares, maximum likelihood and conditional least squares. The results suggest that although the tests based on these estimators are asymptotically equivalent for particular models and parameter values, their sampling properties for samples of the size commonly found in economic applications can differ substantially, because of differences in both finite-sample estimation efficiencies and residual regeneration methods.
源语言英语
页(从-至)527-541
期刊Journal of Time Series Analysis
26
4
DOI
出版状态已出版 - 2005

Corresponding author email

yfang@darkwing.uoregon.edu

关键词

  • Autoregressive-moving average model
  • conditional least squares
  • goodness-of-fit test
  • maximum likelihood
  • partial autocorrelation
  • residual autocorrelation
  • unconditional least squares

成果物的来源

  • SCI

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