Nearest neighbor conditional estimation for Harris recurrent Markov chains

Alessio Sancetta

Journal of Multivariate Analysis, 2009, vol. 100, issue 10, 2224-2236

Abstract: This paper is concerned with consistent nearest neighbor time series estimation for data generated by a Harris recurrent Markov chain on a general state space. It is shown that nearest neighbor estimation is consistent in this general time series context, using simple and weak conditions. The results proved here, establish consistency, in a unified manner, for a large variety of problems, e.g. autoregression function estimation, and, more generally, extremum estimators as well as sequential forecasting. Finally, under additional conditions, it is also shown that the estimators are asymptotically normal.

Keywords: Markov; chain; Nonparametric; estimation; Semiparametric; estimation; Sequential; forecasting (search for similar items in EconPapers)
Date: 2009
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Related works:
Working Paper: Nearest Neighbor Conditional Estimation for Harris Recurrent Markov Chains (2007)
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