Local Polynomial Regression

By J. Fox. 2000

49 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

UNIFORM BAHADUR REPRESENTATION FOR LOCAL POLYNOMIAL ESTIMATES OF M-REGRESSION AND ITS APPLICATION TO THE ADDITIVE MODEL (2007, unknown): “However, the limitations of this estimator are manyfold and there are good theoretical reasons for working instead with the local polynomial class of estimators (Fan and Gijbels, 1996).”
The Generalized Oaxaca-Blinder Estimator (2020, background): “In the survey sampling literature, that estimator is known as the generalized difference estimator (Cassel, Sarndal, and Wretman 1976; Breidt and Opsomer 2017). The idea of using fitted values in an OLS regression has also appeared before in the survey sampling community, under the name “model calib”
Efficiency, subsidies and environmental adaptation of animal farming under CAP (2005, background): “Consistency, asymptotic theory and properties are well known and studied for the multivariate case in Ruppert and Wand (1994), for a general introduction see Fan and Gijbels (1996). If we eliminate in equation (12) the vector a1 and thus maximize only over a0, the minimizing argument is a local cons”