We study a novel large dimensional approximate factor model with regime changes in the
loadings driven by a latent first order Markov process. By exploiting the equivalent linear …

Matrix-valued time series data are widely available in various applications, attracting
increasing attention in the literature. However, while nonlinearity has been recognized, the …

Multi-dimensional time series data, such as matrix and tensor-variate time series, are
increasingly prevalent in fields such as economics, finance, and climate science. Traditional …

High-dimensional matrix-valued time series are of significant interest in economics and
finance, with prominent examples including cross region macroeconomic panels and firms' …

Large-scale matrix data has been widely discovered and continuously studied in various
fields recently. Considering the multi-level factor structure and utilizing the matrix structure …

This paper considers estimation of and testing for a class of locally stationary time series
factor models with evolutionary dynamics, where the entries and dimension of the factor …