On the asymptotic normality of estimates in the nearly non-stationary AR(1) models

DOI10.1007/BF02986860zbMath0897.60026OpenAlexW2041911449MaRDI QIDQ1381645

Alfredas Račkauskas, Kęstutis Kubilius

Publication date: 1 April 1998

Published in: Lithuanian Mathematical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02986860

zbMATH Keywords

moment conditionsAR(1) processesclasses of noisesrate of normal approximation

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05)

Cites Work

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• Asymptotic properties of multivariate nonstationary processes with applications to autoregressions
• Asymptotic inference for nearly nonstationary AR(1) processes
• Maximum likelihood type estimation for nearly nonstationary autoregressive time series
• On the asymptotic accuracy of least-squares estimators in nearly unstable AR(1) processes
• Rate of convergence in the invariance principle for martingale difference arrays
• On the accuracy of normal approximation in the invariance principle
• The Limiting Distribution of the Serial Correlation Coefficient in the Explosive Case
• An exact rate of convergence in the functional central limit theorem for special martingale difference arrays
• Towards a unified asymptotic theory for autoregression
• An approximation of partial sums of independent RV's, and the sample DF. II
• Probability Inequalities for Sums of Independent Random Variables

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