Kernel regression estimates of growth curves using nonstationary correlated errors
AbstractWe 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Elsevier in its journal Statistics & Probability Letters.
Volume (Year): 34 (1997)
Issue (Month): 4 (June)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hart, Jeffrey D. & Wehrly, Thomas E., 1993. "Consistency of cross-validation when the data are curves," Stochastic Processes and their Applications, Elsevier, Elsevier, vol. 45(2), pages 351-361, April.
- Altman, Naomi Simone, 1993. "Estimating error correlation in nonparametric regression," Statistics & Probability Letters, Elsevier, Elsevier, vol. 18(3), pages 213-218, October.
- Karim Benhenni & Mustapha Rachdi & Yingcai Su, 2013. "The effect of the regularity of the error process on the performance of kernel regression estimators," Metrika, Springer, Springer, vol. 76(6), pages 765-781, August.
- Vicente NÃºÃ±ez-AntÃ³n & Juan RodrÃguez-PÃ³o & Philippe Vieu, 1999. "Longitudinal data with nonstationary errors: a nonparametric three-stage approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, Springer, vol. 8(1), pages 201-231, June.
- Benhenni, K. & Rachdi, M., 2006. "Nonparametric estimation of the regression function from quantized observations," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 50(11), pages 3067-3085, July.
- RodrÃguez Poo, Juan M. & NÃºÃ±ez AntÃ³n, Vicente Alfredo & Ferreira GarcÃa, MarÃa Eva, 1999. "Two-Stage Nonparametric Regression for Longitudinal Data," BILTOKI, Universidad del PaÃs Vasco - Departamento de EconomÃa Aplicada III (EconometrÃa y EstadÃstica) 1999-01, Universidad del PaÃs Vasco - Departamento de EconomÃa Aplicada III (EconometrÃa y EstadÃstica).
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.