Using difference-based methods for inference in nonparametric regression with time series errors
We show that difference-based methods can be used to construct simple and explicit estimators of error covariance and autoregressive parameters in nonparametric regression with time series errors. When the error process is Gaussian our estimators are efficient, but they are available well beyond the Gaussian case. As an illustration of their usefulness we show that difference-based estimators can be used to produce a simplified version of time series cross-validation. This new approach produces...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Royal Statistical Society Series B|
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