Estimation in partially linear models

Order n algorithms are developed for computing the estimated mean vector, regression coefficients, standard errors and smoothing parameter selection criteria for Speckman smoothing spline estimators in partially linear models. A difference type variance estimator is proposed and shown to be 3 - cons...

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Bibliographic Details
Published in:Computational statistics & data analysis 1998-11, Vol.29 (1), p.27-34
Main Authors: Eubank, R.L., Kambour, E.L., Kim, J.T., Klipple, K., Reese, C.S., Schimek, M.
Format: Article
Language:English
Subjects:
Exact sciences and technology
Mathematics
Multivariate analysis
Oder n algorithm
Parametric inference
Probability and statistics
Sciences and techniques of general use
Smoothing spline
Speckman estimator
Statistics
Variance estimation
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Summary:Order n algorithms are developed for computing the estimated mean vector, regression coefficients, standard errors and smoothing parameter selection criteria for Speckman smoothing spline estimators in partially linear models. A difference type variance estimator is proposed and shown to be 3 - consistent .
ISSN:0167-9473
1872-7352
DOI:10.1016/S0167-9473(98)00054-1