Kernel regression estimates of growth curves using nonstationary correlated errors
We study the nonparametric estimation of the average growth curve under a very general parametric form of the covariance structure that allows for monotone transformation of the time scale. We also investigate the properties of optimal bandwidth selection methods and compare the results with those obtained under stationarity.
Volume (Year): 34 (1997)
Issue (Month): 4 (June)
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- Altman, Naomi Simone, 1993. "Estimating error correlation in nonparametric regression," Statistics & Probability Letters, Elsevier, vol. 18(3), pages 213-218, October.
- Hart, Jeffrey D. & Wehrly, Thomas E., 1993. "Consistency of cross-validation when the data are curves," Stochastic Processes and their Applications, Elsevier, vol. 45(2), pages 351-361, April.
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