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Estimation of a multiplicative correlation structure in the large dimensional case (Q2190234)

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English	Estimation of a multiplicative correlation structure in the large dimensional case	scientific article

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scholarly article

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Estimation of a multiplicative correlation structure in the large dimensional case (English)

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Christian M. Hafner

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Oliver B. Linton

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Journal of Econometrics

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publication date

18 June 2020

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full work available at URL

https://arxiv.org/abs/1605.04838

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zbMATH Keywords

correlation matrix

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Kronecker product

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matrix logarithm

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multiway array data

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portfolio choice

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describes a project that uses

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MaRDI profile type

MaRDI publication profile

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Array Variate Random Variables with Multiway Kro- necker Delta Covariance Matrix Structure

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Panel Data Models With Interactive Fixed Effects

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Limiting behavior of \(M\)-estimators of regression coefficients in high dimensional linear models. I: Scale-dependent case. II: Scale-invariant case

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One-Step Huber Estimates in the Linear Model

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Covariance regularization by thresholding

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Invariance of covariance structures under groups of transformations

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Optimal rates of convergence for covariance matrix estimation

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Optimal rates of convergence for sparse covariance matrix estimation

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High dimensional generalized empirical likelihood for moment restrictions with dependent data

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OUP accepted manuscript

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Computational Techniques for Real Logarithms of Matrices

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Common risk factors in the returns on stocks and bonds

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High dimensional covariance matrix estimation using a factor model

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High-dimensional covariance matrix estimation in approximate factor models

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Large Covariance Estimation by Thresholding Principal Orthogonal Complements

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Nonlinear time series. Nonparametric and parametric methods

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Separable factor analysis with applications to mortality data

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Equivariant minimax dominators of the MLE in the array normal model

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Perturbations of the matrix logarithm

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On parameters of increasing dimensions

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Functions of Matrices

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Separable covariance arrays via the Tucker product, with applications to multivariate relational data

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Multilinear tensor regression for longitudinal relational data

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Equivariant and scale-free Tucker decomposition models

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Matrix Analysis

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Robust regression: Asymptotics, conjectures and Monte Carlo

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A well-conditioned estimator for large-dimensional covariance matrices

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Nonlinear shrinkage estimation of large-dimensional covariance matrices

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Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions

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Classification of Higher-order Data with Separable Covariance and Structured Multiplicative or Additive Mean Models

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Sparse Matrix Graphical Models

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Prediction of multivariate time series by autoregressive model fitting

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Estimating structured correlation matrices in smooth Gaussian random field models.

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Asymptotics with increasing dimension for robust regression with applications to the bootstrap

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Maximum likelihood estimation for the tensor normal distribution: Algorithm, minimum sample size, and empirical bias and dispersion

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Dependent central limit theorems and invariance principles

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A Bernstein type inequality and moderate deviations for weakly dependent sequences

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The asymptotic variance matrix of the sample correlation matrix

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High-dimensional semiparametric bigraphical models

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The multilinear normal distribution: introduction and some basic properties

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Testing Hypotheses About the Number of Factors in Large Factor Models

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Estimating the quadratic covariation matrix for asynchronously observed high frequency stock returns corrupted by additive measurement error

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Linear Regression Limit Theory for Nonstationary Panel Data

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Asymptotic behavior of M estimators of p regression parameters when \(p^ 2/n\) is large. II: Normal approximation

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More on the Kronecker Structured Covariance Matrix

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On asymptotically optimal confidence regions and tests for high-dimensional models

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Asymptotic Statistics

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Weak convergence and empirical processes. With applications to statistics

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The ubiquitous Kronecker product

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How close is the sample covariance matrix to the actual covariance matrix?

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Hierarchical array priors for ANOVA decompositions of cross-classified data

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Testing for Nodal Dependence in Relational Data Matrices

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Asymptotics of empirical eigenstructure for high dimensional spiked covariance

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On M-processes and M-estimation

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Performance bounds for parameter estimates of high-dimensional linear models with correlated errors

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Large Sample Covariance Matrices and High-Dimensional Data Analysis

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Model selection and estimation in the matrix normal graphical model

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Asymptotic behavior of M-estimators for the linear model

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Identifiers

zbMATH Open document ID

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10.1016/j.jeconom.2019.12.012

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Mathematics Subject Classification ID

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zbMATH DE Number

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Sitelinks

Mathematics(1 entry)

mardi Publication:2190234

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