Bootstrap inference in functional linear regression models with scalar response under heteroscedasticity
From MaRDI portal
Publication:6635567
DOI10.1214/24-ejs2285MaRDI QIDQ6635567
Daniel J. Nordman, Xiongtao Dai, Hyemin Yeon
Publication date: 12 November 2024
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
asymptotic normalitymultiple testingbias correctionfunctional data analysisscalar-on-function regressionbootstrapping pairs
Asymptotic distribution theory in statistics (62E20) Functional data analysis (62R10) Nonparametric statistical resampling methods (62G09)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Minimax adaptive tests for the functional linear model
- Bootstrap in functional linear regression
- Prediction in functional linear regression
- On properties of percentile bootstrap confidence intervals for prediction in functional linear regression
- Measure theory and probability theory.
- Methodology and convergence rates for functional linear regression
- Bootstrapping regression models
- Bootstrapping \(M\)-estimators of a multiple linear regression parameter
- Comparing nonparametric versus parametric regression fits
- On bootstrapping \(M\)-estimated residual processes in multiple linear regression models
- Resampling methods for dependent data
- High-dimensional simultaneous inference with the bootstrap
- Functional linear model
- Weighted least squares methods for prediction in the functional data linear model
- Bootstrap and wild bootstrap for high dimensional linear models
- Generalized functional linear models
- Asymptotics of prediction in functional linear regression with functional outputs
- Functional data analysis.
- Classical testing in functional linear models
- On asymptotic distribution of prediction in functional linear regression
- Asymptotic properties of the residual bootstrap for Lasso estimators
- Bootstrapping Lasso Estimators
- On the validity of the pairs bootstrap for lasso estimators
- Functional Generalized Linear Models with Images as Predictors
- Bootstrapping robust regression
- Testing for No Effect in Functional Linear Regression Models, Some Computational Approaches
- Testing Hypotheses in the Functional Linear Model
- Testing for Marginal Linear Effects in Quantile Regression
- Minimax and Adaptive Prediction for Functional Linear Regression
- Adaptive Global Testing for Functional Linear Models
- Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
- Hypothesis testing in functional linear models
- On bootstrapping the mode in the nonparametric regression model with random design
- Functional linear regression for discretely observed data: from ideal to reality
- Bootstrap inference in functional linear regression models with scalar response
This page was built for publication: Bootstrap inference in functional linear regression models with scalar response under heteroscedasticity