Prediction and nonparametric estimation for time series analysis with heavy tails
Motivated by prediction problems for time series with heavy-tailed marginal distributions, we consider methods based on 'local least absolute deviations' for estimating a regression median from dependent data. Unlike more conventional 'local median' methods, which are in effect based on locally fitting a polynomial of degree 0, techniques founded on local least absolute deviations have quadratic bias right up to the boundary of the design interval. Also in contrast to local least-squares...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Time Series Analysis|
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