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UNIFORM CONSISTENCY FOR NONPARAMETRIC ESTIMATORS IN NULL RECURRENT TIME SERIES

  • Jiti Gao (a1), Shin Kanaya (a2), Degui Li (a3) and Dag Tjøstheim (a4)

Abstract

This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains. Under suitable regularity conditions, we derive uniform convergence rates of the estimators. Our results can be viewed as a nonstationary extension of some well-known uniform consistency results for stationary time series.

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*Address correspondence to Jiti Gao, Department of Econometrics and Business Statistics, Monash University, Caulfield East, VIC 3145, Australia; e-mail: jiti.gao@monash.edu.

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UNIFORM CONSISTENCY FOR NONPARAMETRIC ESTIMATORS IN NULL RECURRENT TIME SERIES

  • Jiti Gao (a1), Shin Kanaya (a2), Degui Li (a3) and Dag Tjøstheim (a4)

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