Academic Journal

Model Testing Based on Regression Spline

Bibliographic Details
Title: Model Testing Based on Regression Spline
Authors: Li, Na
Source: MODID-6d55e02e354:IntechOpen
Publisher Information: IntechOpen
Publication Year: 2018
Subject Terms: Computers / Programming / Algorithms, bisacsh:COM051300
Description: Tests based on regression spline are developed in this chapter for testing nonparametric functions in nonparametric, partial linear and varying-coefficient models, respectively. These models are more flexible than linear regression model. However, one important problem is if it is really necessary to use such complex models which contain nonparametric functions. For this purpose, p-values for testing the linearity and constancy of the nonparametric functions are established based on regression spline and fiducial method. In the application of spline-based method, the determination of knots is difficult but plays an important role in inferring regression curve. In order to infer the nonparametric regression at different smoothing levels (scales) and locations, multi-scale smoothing methods based on regression spline are developed to test the structures of the regression curve and compare multiple regression curves. It could sidestep the determination of knots; meanwhile, it could give a more reliable result in using the spline-based method.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
ISBN: 978-1-78923-250-9
1-78923-250-3
DOI: 10.5772/intechopen.74858
Availability: https://openresearchlibrary.org/viewer/a7235dc2-d16e-4854-9826-ddafe3524afd
https://openresearchlibrary.org/ext/api/media/a7235dc2-d16e-4854-9826-ddafe3524afd/assets/external_content.pdf
https://doi.org/10.5772/intechopen.74858
Rights: https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number: edsbas.127B23C8
Database: BASE
Description
ISBN:9781789232509
1789232503
DOI:10.5772/intechopen.74858