Cover Image

Spectral estimation for high-dimensional linear processes

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Namdari, Jamshid, Aue, Alexander, Paul, Debashis
Format:	Preprint
Published:	2025
Subjects:	Statistics Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Limiting Spectral Distribution of a Random Commutator Matrix
by: Hazarika, Javed, et al.
Published: (2024)

Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes
by: Kühnert, Sebastian, et al.
Published: (2024)

Universality of estimators for high-dimensional linear models with block dependency
by: Tsuda, Toshiki, et al.
Published: (2024)

Consistency of heritability estimation from summary statistics in high-dimensional linear models
by: Azriel, David, et al.
Published: (2025)

Meta-Learning with Generalized Ridge Regression: High-dimensional Asymptotics, Optimality and Hyper-covariance Estimation
by: Jin, Yanhao, et al.
Published: (2024)

Kernel entropy estimation for linear processes II
by: Xiong, Yudan, et al.
Published: (2024)

Sampling effects on Lasso estimation of drift functions in high-dimensional diffusion processes
by: Amorino, Chiara, et al.
Published: (2024)

Sparse estimation for the drift of high-dimensional Ornstein--Uhlenbeck processes with i.i.d. paths
by: Nakakita, Shogo
Published: (2025)

LSD of the Commutator of two data Matrices
by: Hazarika, Javed, et al.
Published: (2025)

Spectral properties of high dimensional rescaled sample correlation matrices
by: Chen, Weijiang, et al.
Published: (2024)

Detecting Spectral Breaks in Spiked Covariance Models
by: Dörnemann, Nina, et al.
Published: (2024)

Properties of stepwise parameter estimation in high-dimensional vine copulas
by: Gauss, Jana, et al.
Published: (2025)

Robust estimation for high-dimensional time series with heavy tails
by: Wang, Yu, et al.
Published: (2024)

Concentration inequalities for high-dimensional linear processes with dependent innovations
by: Mendes, Eduardo Fonseca, et al.
Published: (2023)

Estimation in linear high dimensional Hawkes processes: a Bayesian approach
by: Rousseau, Judith, et al.
Published: (2025)

CLT in high-dimensional Bayesian linear regression with low SNR
by: Lee, Seunghyun, et al.
Published: (2025)

A minimax optimal approach to high-dimensional double sparse linear regression
by: Zhang, Yanhang, et al.
Published: (2023)

Bitcoin Forecasting with Classical Time Series Models on Prices and Volatility
by: Kareem, Anmar, et al.
Published: (2025)

Optimal covariance matrix estimation for high-dimensional noise in high-frequency data
by: Chang, Jinyuan, et al.
Published: (2018)

On a class of high dimensional linear regression methods with debiasing and thresholding
by: Wang, Ying-Ao, et al.
Published: (2025)

Empirical Bayes inference in sparse high-dimensional generalized linear models
by: Tang, Yiqi, et al.
Published: (2023)

Convergence of covariance and spectral density estimates for high-dimensional functional time series
by: Li, Bufan, et al.
Published: (2025)

Contraction rates and projection subspace estimation with Gaussian process priors in high dimension
by: Odin, Elie, et al.
Published: (2024)

Spectral analysis of high-dimensional spot volatility matrix with applications
by: Liu, Qiang, et al.
Published: (2025)

An operator-level ARCH Model
by: Aue, Alexander, et al.
Published: (2026)

Support estimation in high-dimensional heteroscedastic mean regression
by: Hermann, Philipp, et al.
Published: (2020)

Detection and inference of changes in high-dimensional linear regression with non-sparse structures
by: Cho, Haeran, et al.
Published: (2024)

Dimension estimation in PCA model using high-dimensional data augmentation
by: Radojicic, Una, et al.
Published: (2025)

Weight-calibrated estimation for factor models of high-dimensional time series
by: Qiao, Xinghao, et al.
Published: (2025)

Nonparametric estimation of linear multiplier for processes driven by a Hermite process
by: Rao, B. L. S. Prakasa
Published: (2026)

Bayesian high-dimensional covariate selection in non-linear mixed-effects models using the SAEM algorithm
by: Naveau, Marion, et al.
Published: (2022)

Parametric Mean-Field empirical Bayes in high-dimensional linear regression
by: Lee, Seunghyun, et al.
Published: (2026)

On estimation of skewed stable linear regression
by: Kawamo, Eitaro, et al.
Published: (2024)

Covariance scanning for adaptively optimal change point detection in high-dimensional linear models
by: Cho, Haeran, et al.
Published: (2025)

LSD of sample covariances of superposition of matrices with separable covariance structure
by: Hazarika, Javed, et al.
Published: (2025)

Bayes optimal learning in high-dimensional linear regression with network side information
by: Nandy, Sagnik, et al.
Published: (2023)

Spectral analysis of multivariate stationary Hawkes processes
by: Tang, Yifu, et al.
Published: (2026)

New Berry-Esseen bounds for parameter estimation of Gaussian processes observed at high frequency
by: Es-Sebaiy, Khalifa, et al.
Published: (2026)

Nonparametric estimation of linear multiplier for processes driven by a bifractional Brownian motion
by: Rao, B. L. S. Prakasa
Published: (2024)

Statistical inference using debiased group graphical lasso for multiple sparse precision matrices
by: Bhowal, Sayan Ranjan, et al.
Published: (2025)