scientific article; zbMATH DE number 7376780
From MaRDI portal
Publication:5004058
zbMath1470.62108MaRDI QIDQ5004058
Publication date: 30 July 2021
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nonparametric hypothesis testing (62G10) Functional data analysis (62R10) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Measures of association (correlation, canonical correlation, etc.) (62H20)
Related Items (7)
Variable selection for functional linear models with strong heredity constraint ⋮ Sparse Functional Principal Component Analysis in High Dimensions ⋮ Finite sample theory for high-dimensional functional/scalar time series with applications ⋮ Model selection for functional linear regression with hierarchical structure ⋮ Distribution/correlation-free test for two-sample means in high-dimensional functional data with eigenvalue decay relaxed ⋮ An autocovariance-based learning framework for high-dimensional functional time series ⋮ From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- On asymptotically optimal confidence regions and tests for high-dimensional models
- Functional linear regression analysis for longitudinal data
- Nearly unbiased variable selection under minimax concave penalty
- Minimax adaptive tests for the functional linear model
- Gaussian approximation of suprema of empirical processes
- Optimal computational and statistical rates of convergence for sparse nonconvex learning problems
- A general theory of hypothesis tests and confidence regions for sparse high dimensional models
- A reproducing kernel Hilbert space approach to functional linear regression
- Some sharp performance bounds for least squares regression with \(L_1\) regularization
- High-dimensional variable selection
- Prediction in functional linear regression
- Functional additive regression
- Methodology and convergence rates for functional linear regression
- Lasso-type recovery of sparse representations for high-dimensional data
- Functional linear model
- Asymptotics for Lasso-type estimators.
- A significance test for the lasso
- Generalized functional linear models
- Simultaneous analysis of Lasso and Dantzig selector
- High-dimensional generalized linear models and the lasso
- Calibrating nonconvex penalized regression in ultra-high dimension
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Functional data analysis.
- High-dimensional graphs and variable selection with the Lasso
- Strong oracle optimality of folded concave penalized estimation
- Nonparametric inference in generalized functional linear models
- Statistical inferences for functional data
- Partially functional linear regression in high dimensions
- Functional partial linear model
- Functional Principal Component Regression and Functional Partial Least Squares
- Regression Analysis for a Functional Response
- Testing Hypotheses in the Functional Linear Model
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Testing and Confidence Intervals for High Dimensional Proportional Hazards Models
- Sparse Additive Models
- Stability Selection
- Minimax and Adaptive Prediction for Functional Linear Regression
- Linear functional regression: The case of fixed design and functional response
- Principal component estimation of functional logistic regression: discussion of two different approaches
- Shrinkage estimation and selection for multiple functional regression
- Adaptive Global Testing for Functional Linear Models
- Variable Selection with Error Control: Another Look at Stability Selection
- Nonconcave Penalized Likelihood With NP-Dimensionality
- Functional Additive Models
- Model Selection and Estimation in Regression with Grouped Variables
- On Properties of Functional Principal Components Analysis
- Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
- Structured Functional Additive Regression in Reproducing Kernel Hilbert Spaces
- Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
This page was built for publication:
