On the optimal choice of the number of empirical Fourier coefficients for comparison of regression curves

DOI10.1007/s00362-014-0619-1zbMath1327.62265OpenAlexW2051535194MaRDI QIDQ894856

N. E. Zubov

Publication date: 24 November 2015

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-014-0619-1

zbMATH Keywords

adaptive testsempirical Fourier coefficientstesting for functional data

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10)

Related Items (3)

On linear regression models in infinite dimensional spaces with scalar response ⋮ D-optimal designs for full and reduced Fourier regression models ⋮ Multivariate small sample tests for two-way designs with applications to industrial statistics

Uses Software

• fda (R)

Cites Work

• Testing the equality of nonparametric regression curves based on Fourier coefficients
• Bandwidth choice for nonparametric regression
• Semiparametric comparison of regression curves
• Testing goodness-of-fit in regression via order selection criteria
• Nonparametric comparison of several regression functions: Exact and asymptotic theory
• Functional data analysis
• Nonparametric comparison of regression curves: An empirical process approach
• Testing the equality of nonparametric regression curves
• Bootstrap tests for nonparametric comparison of regression curves with dependent errors
• Two-Sample Test Against One-Sided Alternatives
• Smoothing Parameter Selection for Power Optimality in Testing of Regression Curves
• Bootstrap Test for Difference Between Means in Nonparametric Regression

This page was built for publication: On the optimal choice of the number of empirical Fourier coefficients for comparison of regression curves