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- W2085514238 abstract "The generalised cross-validation criterion for choosing the degree of smoothing in spline regression is extended to accommodate an autocorrelated error sequence. It is demonstrated via simulation that the minimum generalised cross-validation smoothing spline is an inconsistent estimator in the presence of autocorrelated errors and that ignoring even moderate autocorrelation structure can seriously affect the performance of the cross-validated smoothing spline. The method of penalised maximum likelihood is used to develop an efficient algorithm for the case in which the autocorrelation decays exponentially. An application of the method to a published data-set is described. The method does not require the data to be equally spaced in time." @default.
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- W2085514238 date "1989-03-01" @default.
- W2085514238 modified "2023-10-11" @default.
- W2085514238 title "ON SPLINE SMOOTHING WITH AUTOCORRELATED ERRORS" @default.
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- W2085514238 doi "https://doi.org/10.1111/j.1467-842x.1989.tb00510.x" @default.
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