Polynomial spline estimation for partial functional linear regression models

DOI10.1007/s00180-015-0636-0zbMath1347.65036OpenAlexW2227516623MaRDI QIDQ311319

Zhao Chen, Jianjun Zhou, Qingyan Peng

Publication date: 29 September 2016

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-015-0636-0

zbMATH Keywords

asymptotic normalityrates of convergencefunctional data analysispolynomial spline

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Related Items

Robust estimation with a modified Huber's loss for partial functional linear models based on splines ⋮ Robust estimation for partial functional linear regression models based on FPCA and weighted composite quantile regression ⋮ Rank-based estimation in varying coefficient partially functional linear regression models ⋮ Test for the parametric part in partial functional linear regression based on B-spline ⋮ Partial functional linear regression with autoregressive errors ⋮ Robust exponential squared loss-based estimation in semi-functional linear regression models ⋮ Robust estimation for partial functional linear regression model based on modal regression ⋮ Composite quantile estimation in partial functional linear regression model based on polynomial spline ⋮ Regularised forecasting via smooth-rough partitioning of the regression coefficients ⋮ Estimation for functional partial linear models with missing responses ⋮ Composite quantile estimation in partial functional linear regression model with dependent errors ⋮ Statistical inference in the partial functional linear expectile regression model

Uses Software

• fda (R)

Cites Work

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