scholarly journals Local polynomial estimation of the mean function and its derivatives based on functional data and regular designs

2014 ◽  
Vol 18 ◽  
pp. 881-899 ◽  
Author(s):  
Karim Benhenni ◽  
David Degras
Test ◽  
2011 ◽  
Vol 20 (3) ◽  
pp. 653-677 ◽  
Author(s):  
Han-Ying Liang ◽  
Jacobo de Uña-Álvarez ◽  
María del Carmen Iglesias-Pérez

2020 ◽  
pp. 1-45
Author(s):  
Feng Yao ◽  
Taining Wang

We propose a nonparametric test of significant variables in the partial derivative of a regression mean function. The derivative is estimated by local polynomial estimation and the test statistic is constructed through a variation-based measure of the derivative in the direction of variables of interest. We establish the asymptotic null distribution of the test statistic and demonstrate that it is consistent. Motivated by the null distribution, we propose a wild bootstrap test, and show that it exhibits the same null distribution, whether the null is valid or not. We perform a Monte Carlo study to demonstrate its encouraging finite sample performance. An empirical application is conducted showing how the test can be applied to infer certain aspects of regression structures in a hedonic price model.


2002 ◽  
Vol 18 (2) ◽  
pp. 227-241 ◽  
Author(s):  
Jan Beran ◽  
Yuanhua Feng ◽  
Sucharita Ghosh ◽  
Philipp Sibbertsen

Statistics ◽  
1997 ◽  
Vol 30 (2) ◽  
pp. 127-148 ◽  
Author(s):  
M. Aerts ◽  
I. Augustyns ◽  
P. Janssen

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