High dimensional generalized linear models for temporal dependent data

Publication date: 19 December 2022

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/journals/bernoulli/volume-29/issue-1/High-dimensional-generalized-linear-models-for-temporal-dependent-data/10.3150/21-BEJ1451.full

zbMATH Keywords

time series analysis robust estimation generalized linear model support recovery high-dimensional analysis

Mathematics Subject Classification ID

Linear inference, regression (62Jxx) Parametric inference (62Fxx) Inference from stochastic processes (62Mxx)

Related Items (2)

Rate-optimal robust estimation of high-dimensional vector autoregressive models ⋮ High dimensional generalized linear models for temporal dependent data

Uses Software

FinTS
SparseLOGREG
PyHawkes

Cites Work

Regularized estimation in sparse high-dimensional time series models
Geometric median and robust estimation in Banach spaces
Oracle inequalities for the lasso in the Cox model
Statistics for high-dimensional data. Methods, theory and applications.
A Bernstein type inequality and moderate deviations for weakly dependent sequences
Support recovery without incoherence: a case for nonconvex regularization
A shrinkage principle for heavy-tailed data: high-dimensional robust low-rank matrix recovery
Empirical risk minimization for heavy-tailed losses
$M$-estimation of linear models with dependent errors
A Bennett concentration inequality and its application to suprema of empirical processes
Gaussian approximation for high dimensional time series
I-LAMM for sparse learning: simultaneous control of algorithmic complexity and statistical error
About the constants in Talagrand's concentration inequalities for empirical processes.
Challenging the empirical mean and empirical variance: a deviation study
Statistical consistency and asymptotic normality for high-dimensional robust $M$-estimators
High dimensional generalized linear models for temporal dependent data
Generalized high-dimensional trace regression via nuclear norm regularization
Simultaneous analysis of Lasso and Dantzig selector
High-dimensional generalized linear models and the lasso
Covariance and precision matrix estimation for high-dimensional time series
Asymptotic spectral theory for nonlinear time series
On linear processes with dependent innovations
On the subspaces of $L^p$ $(p > 2)$ spanned by sequences of independent random variables
Adaptive Lasso and group-Lasso for functional Poisson regression
Asymptotic Equivalence of Regularization Methods in Thresholded Parameter Space
Minimax Optimal Rates for Poisson Inverse Problems With Physical Constraints
Sequential Anomaly Detection in the Presence of Noise and Limited Feedback
The Future of Data Analysis
The Group Lasso for Logistic Regression
The Influence Curve and Its Role in Robust Estimation
Robust Inference for Generalized Linear Models
Compressed Sensing Performance Bounds Under Poisson Noise
Performance Bounds for Expander-Based Compressed Sensing in Poisson Noise
Regularized Estimation of Linear Functionals of Precision Matrices for High-Dimensional Time Series
Non-Parametric Sparse Additive Auto-Regressive Network Models
Limit theorems for iterated random functions
High-dimensional Linear Regression for Dependent Data with Applications to Nowcasting
Learning High-Dimensional Generalized Linear Autoregressive Models
Network Estimation From Point Process Data
Minimax Rates of Estimation for High-Dimensional Linear Regression Over $\ell_q$-Balls
Estimation of High Dimensional Mean Regression in the Absence of Symmetry and Light Tail Assumptions
Robust and consistent variable selection in high-dimensional generalized linear models
Nonlinear system theory: Another look at dependence
Estimation And Selection Via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications
Robust-BD estimation and inference for varying-dimensional general linear models
Robust Estimation of a Location Parameter
A General Qualitative Definition of Robustness
Analysis of Financial Time Series
Quasi-likelihood and/or robust estimation in high dimensions
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers
Performance bounds for parameter estimates of high-dimensional linear models with correlated errors
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