Local Polynomial Smoothing

Measuring the Discrepancy of a Parametric Model via Local Polynomial Smoothing

Scandinavian Journal of Statistics ◽

10.1111/j.1467-9469.2012.00821.x ◽

2012 ◽

Vol 40 (3) ◽

pp. 455-470

Author(s):

ANOUAR EL GHOUCH ◽

MARC G. GENTON ◽

TAOUFIK BOUEZMARNI

Keyword(s):

Parametric Model ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Polynomial Smoothing

Multiscale Local Polynomial Smoothing in a Lifted Pyramid for Non-Equispaced Data

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2012.2225059 ◽

2013 ◽

Vol 61 (3) ◽

pp. 545-555 ◽

Cited By ~ 10

Author(s):

Maarten Jansen

Keyword(s):

Local Polynomial Smoothing ◽

Local Polynomial ◽

Polynomial Smoothing

Fixed design local polynomial smoothing and bandwidth selection for right censored data

Computational Statistics & Data Analysis ◽

10.1016/j.csda.2020.107064 ◽

2021 ◽

Vol 153 ◽

pp. 107064

Author(s):

Dimitrios Bagkavos ◽

Dimitrios Ioannides

Keyword(s):

Censored Data ◽

Bandwidth Selection ◽

Right Censored Data ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Fixed Design ◽

Selection For ◽

Polynomial Smoothing

Binary quantile regression with local polynomial smoothing

Journal of Econometrics ◽

10.1016/j.jeconom.2015.06.019 ◽

2015 ◽

Vol 189 (1) ◽

pp. 24-40 ◽

Cited By ~ 1

Author(s):

Songnian Chen ◽

Hanghui Zhang

Keyword(s):

Quantile Regression ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Polynomial Smoothing ◽

Binary Quantile Regression

Nonlinear regression checking via local polynomial smoothing with applications to thermogravimetric analysis

Journal of Chemometrics ◽

10.1002/cem.1227 ◽

2009 ◽

Vol 23 (6) ◽

pp. 275-282 ◽

Cited By ~ 2

Author(s):

Ricardo Cao ◽

Salvador Naya

Keyword(s):

Thermogravimetric Analysis ◽

Nonlinear Regression ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Polynomial Smoothing

A three-step estimation procedure using local polynomial smoothing for inconsistently sampled longitudinal data

Statistics in Medicine ◽

10.1002/sim.6978 ◽

2016 ◽

Vol 35 (20) ◽

pp. 3613-3622 ◽

Cited By ~ 1

Author(s):

Lei Ye ◽

Ada O. Youk ◽

Susan M. Sereika ◽

Stewart J. Anderson ◽

Lora E. Burke

Keyword(s):

Longitudinal Data ◽

Estimation Procedure ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Polynomial Smoothing

PROPERTIES OF DOUBLY ROBUST ESTIMATORS WHEN NUISANCE FUNCTIONS ARE ESTIMATED NONPARAMETRICALLY

Econometric Theory ◽

10.1017/s0266466618000385 ◽

2018 ◽

Vol 35 (05) ◽

pp. 1048-1087 ◽

Cited By ~ 4

Author(s):

Christoph Rothe ◽

Sergio Firpo

Keyword(s):

Orthogonality Condition ◽

Robust Estimators ◽

Dimensional Parameter ◽

Local Polynomial Smoothing ◽

Local Polynomial ◽

Finite Dimensional ◽

Wide Range ◽

Polynomial Smoothing ◽

Doubly Robust

An estimator of a finite-dimensional parameter is said to be doubly robust (DR) if it imposes parametric specifications on two unknown nuisance functions, but only requires that one of these two specifications is correct in order for the estimator to be consistent for the object of interest. In this article, we study versions of such estimators that use local polynomial smoothing for estimating the nuisance functions. We show that such semiparametric two-step (STS) versions of DR estimators have favorable theoretical and practical properties relative to other commonly used STS estimators. We also show that these gains are not generated by the DR property alone. Instead, it needs to be combined with an orthogonality condition on the estimation residuals from the nonparametric first stage, which we show to be satisfied in a wide range of models.