Backfitting versus profiling in general criterion functions Academic Article

abstract

• We study the backfitting and profile methods for general criterion functions that depend on a parameter of interest and a nuisance function 9. We show that when different amounts of smoothing are employed for each method to estimate the function , the two estimation procedures produce estimators of with the same limiting distributions, even when the criterion functions are non-smooth in and/or . The results are applied to a partially linear median regression model and a change point model, both examples of non-smooth criterion functions.

authors

• Carroll, Raymond

published proceedings

• STATISTICA SINICA

author list (cited authors)

• Van Keilegom, I., & Carroll, R. J.

complete list of authors

• Van Keilegom, Ingrid||Carroll, Raymond J

publication date

• April 2007

published in

• STATISTICA SINICA  Journal

keywords

• Backfitting
• Change Points
• Dioxin
• Kernel Estimation
• Median Regression
• Nonparametric Regression
• Partially Linear Model
• Profile Kernel Methods
• Semiparametric Estimation
• Undersmoothing

start page

• 797

end page

• 816

volume

• 17

issue

• 2