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Asymptotic Properties of Conditional Least-squares Estimators for Array Time Series

Author

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  • Guy Melard
  • Rajae Azrak

Abstract

The paper provides a kind of Klimko-Nelson theoremsalternative in the case of conditional estimators for array timeseries, when the assumptions of almost sure convergence cannot be established.We do not assume stationarity nor even local stationarity.In addition, we provide sufficient conditions for two of the assumptionsand two theorems for the evaluation of the information matrixin array time series.

Suggested Citation

  • Guy Melard & Rajae Azrak, 2017. "Asymptotic Properties of Conditional Least-squares Estimators for Array Time Series," Working Papers ECARES ECARES 2017-49, ULB -- Universite Libre de Bruxelles.
  • Handle: RePEc:eca:wpaper:2013/263350
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    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/263350/3/2017-49-AZRAK_MELARD-asymptomatic.pdf
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    Cited by:

    1. Rajae Azrak & Guy Melard, 2017. "Autoregressive Models with Time-dependent Coefficients. A comparison between Several Approaches," Working Papers ECARES ECARES 2017-48, ULB -- Universite Libre de Bruxelles.

    More about this item

    Keywords

    properties least-square array time series;

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