High-dimensional inference for linear model with correlated errors
type: Item
instance of: scholarly article
title: High-dimensional inference for linear model with correlated errors
author: Panxu Yuan
author: Xiao Guo
published in: Metrika
publication date: 2022-02-11T00:00:00Z
Mathematics Subject Classification ID: 62-XX
zbMATH DE Number: 7472639
zbMATH Keywords: correlated errors
zbMATH Keywords: desparsifying Lasso
zbMATH Keywords: functional dependence measure
zbMATH Keywords: high-dimensional inference
zbMATH Keywords: stationary time series
MaRDI profile type: Publication
full work available at URL: s00184-021-00820-7
OpenAlex ID: W3162783859
cites work: Regularized estimation in sparse high-dimensional time series models
cites work: Regularized estimation of large covariance matrices
cites work: Statistics for high-dimensional data. Methods, theory and applications.
cites work: The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
cites work: Lasso-driven inference in time and space
cites work: Forecasting using a large number of predictors: is Bayesian shrinkage a valid alternative to principal components?
cites work: Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
cites work: A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article)
cites work: Penalized least squares estimation with weakly dependent data
cites work: Q3247378
cites work: A note on the asymptotic distribution of lasso estimator for correlated data
cites work: High-dimensional Linear Regression for Dependent Data with Applications to Nowcasting
cites work: Q5251797
cites work: Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
cites work: ASYMPTOTICS OF SPECTRAL DENSITY ESTIMATES
cites work: Subsampling
cites work: Restricted eigenvalue properties for correlated Gaussian designs
cites work: Asymptotic spectral theory for nonlinear time series
cites work: Q4864293
cites work: On the conditions used to prove oracle results for the Lasso
cites work: On asymptotically optimal confidence regions and tests for high-dimensional models
cites work: High-Dimensional Statistics
cites work: Regression coefficient and autoregressive order shrinkage and selection via the lasso
cites work: Lasso guarantees for \(\beta \)-mixing heavy-tailed time series
cites work: Nonlinear system theory: Another look at dependence
cites work: Q3643299
cites work: Performance bounds for parameter estimates of high-dimensional linear models with correlated errors
cites work: Square‐Root LASSO for High‐Dimensional Sparse Linear Systems with Weakly Dependent Errors
cites work: Nearly unbiased variable selection under minimax concave penalty
cites work: Confidence Intervals for Low Dimensional Parameters in High Dimensional Linear Models
cites work: The Adaptive Lasso and Its Oracle Properties
DOI: 10.1007/S00184-021-00820-7
description: scientific article; zbMATH DE number 7472639