4 papers
Factor-guided estimation of large covariance matrix function with conditional functional sparsity
Dong Li, Xinghao Qiao, Zihan Wang
This paper addresses the fundamental task of estimating covariance matrix functions for high-dimensional functional data/functional time series. We consider two functional factor s…
On a new robust method of inference for general time series models
Zihan Wang, Xinghao Qiao, Dong Li +1
In this article, we propose a novel logistic quasi-maximum likelihood estimation (LQMLE) for general parametric time series models. Compared to the classical Gaussian QMLE and exis…
Large covariance matrix estimation with factor-assisted variable clustering
Dong Li, Xinghao Qiao, Cheng Yu
This paper studies the covariance matrix estimation for high-dimensional time series within a new framework that combines low-rank factor and latent variable-specific cluster struc…
From sparse to dense functional data in high dimensions: Revisiting phase transitions from a non-asymptotic perspective
Shaojun Guo, Dong Li, Xinghao Qiao +1
Nonparametric estimation of the mean and covariance functions is ubiquitous in functional data analysis and local linear smoothing techniques are most frequently used. Zhang and Wa…