Online change-point detection for matrix-valued time series with latent two-way factor structure

Factor analysis and principal components; correspondence analysis (62H25) Sequential statistical analysis (62L10) Statistical aspects of big data and data science (62R07)

Cites Work

Unnamed Item
Unnamed Item
A MOSUM procedure for the estimation of multiple random change points
Testing for (in)finite moments
Projected estimation for large-dimensional matrix factor models
The effect of data transformation on common cycle, cointegration, and unit root tests: Monte Carlo results and a simple test
Factor modeling for high-dimensional time series: inference for the number of factors
On the norming constants for normal maxima
Detecting big structural breaks in large factor models
Testing for factor loading structural change under common breaks
Identification and estimation of a large factor model with structural instability
Testing for structural breaks in dynamic factor models
Simultaneous multiple change-point and factor analysis for high-dimensional time series
Factor models for matrix-valued high-dimensional time series
Testing for randomness in a random coefficient autoregression model
Delay time in sequential detection of change
Monitoring changes in linear models
On the rate of approximations for maximum likelihood tests in change-point models
Rank determination in tensor factor model
Sequential testing for structural stability in approximate factor models
Estimating and testing high dimensional factor models with multiple structural changes
On sequential detection of parameter changes in linear regression
Testing for structural stability of factor augmented forecasting models
Testing and support recovery of correlation structures for matrix-valued observations with an application to stock market data
Quasi-maximum likelihood estimation of break point in high-dimensional factor models
Computational Advertising: Techniques for Targeting Relevant Ads
TESTS FOR PARAMETER INSTABILITY IN DYNAMIC FACTOR MODELS
An approximation of partial sums of independent RV's, and the sample DF. II
An approximation of partial sums of independent RV'-s, and the sample DF. I
On the rate of convergence of normal extremes
A Randomized Sequential Procedure to Determine the Number of Factors
High Dimensional Change Point Estimation via Sparse Projection
Shrinkage Estimation of High-Dimensional Factor Models with Structural Instabilities
Embracing the Blessing of Dimensionality in Factor Models
Monitoring Structural Change
NONPARAMETRIC NONSTATIONARITY TESTS
Identification and estimation of threshold matrix‐variate factor models
A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters
Constrained Factor Models for High-Dimensional Matrix-Variate Time Series
A bootstrap method to test for the existence of finite moments
Determining the Number of Factors in the General Dynamic Factor Model
Inferential Theory for Factor Models of Large Dimensions
Determining the Number of Factors in Approximate Factor Models
High-Dimensional, Multiscale Online Changepoint Detection
Factor Models for High-Dimensional Tensor Time Series
One-way or two-way factor model for matrix sequences?
Inference in Heavy-Tailed Nonstationary Multivariate Time Series
Statistical Inference for High-Dimensional Matrix-Variate Factor Models
Changepoint Detection in Heteroscedastic Random Coefficient Autoregressive Models
The likelihood ratio test for structural changes in factor models
Inference in High-Dimensional Online Changepoint Detection
Inference in Sparsity-Induced Weak Factor Models
Testing for Common Trends in Nonstationary Large Datasets
A New Class of Change Point Test Statistics of Rényi Type

This page was built for publication: Online change-point detection for matrix-valued time series with latent two-way factor structure