42 citations · 140 across the 13 of their papers we have counts for
13 papers
Time-Varying Model Averaging of Multi-layer Network Vector Autoregressions
Degui Li, Yuying Sun, Boyao Wu
In this paper, we introduce a flexible time-varying multi-layer network vector autoregression (VAR) model framework for large-scale time series, allowing agents in dynamic systems…
Estimating Factor-Based Spot Volatility Matrices with Noisy and Asynchronous High-Frequency Data
Degui Li, Oliver Linton, Haoxuan Zhang
We propose a new estimator of high-dimensional spot volatility matrices satisfying a low-rank plus sparse structure from noisy and asynchronous high-frequency data collected for an…
Covariance Function Estimation for High-Dimensional Functional Time Series with Dual Factor Structures
Chenlei Leng, Degui Li, Hanlin Shang +1
We propose a flexible dual functional factor model for modelling high-dimensional functional time series. In this model, a high-dimensional fully functional factor parametrisation…
Nonparametric Estimation of Large Spot Volatility Matrices for High-Frequency Financial Data
Ruijun Bu, Degui Li, Oliver Linton +1
In this paper, we consider estimating spot/instantaneous volatility matrices of high-frequency data collected for a large number of assets. We first combine classic nonparametric k…
Detection and Estimation of Structural Breaks in High-Dimensional Functional Time Series
Degui Li, Runze Li, Han Lin Shang
In this paper, we consider detecting and estimating breaks in heterogeneous mean functions of high-dimensional functional time series which are allowed to be cross-sectionally corr…
Functional-Coefficient Quantile Regression for Panel Data with Latent Group Structure
Xiaorong Yang, Jia Chen, Degui Li +1
This paper considers estimating functional-coefficient models in panel quantile regression with individual effects, allowing the cross-sectional and temporal dependence for large p…
Estimation of Grouped Time-Varying Network Vector Autoregression Models
Degui Li, Bin Peng, Songqiao Tang +1
This paper introduces a flexible time-varying network vector autoregressive model framework for large-scale time series. A latent group structure is imposed on the heterogeneous an…
Estimating Time-Varying Networks for High-Dimensional Time Series
Jia Chen, Degui Li, Yuning Li +1
We explore time-varying networks for high-dimensional locally stationary time series, using the large VAR model framework with both the transition and (error) precision matrices ev…
Dimension Reduction and MARS
Yu Liu, Degui Li, Yingcun Xia
The multivariate adaptive regression spline (MARS) is one of the popular estimation methods for nonparametric multivariate regressions. However, as MARS is based on marginal spline…
Estimation in nonlinear regression with Harris recurrent Markov chains
Degui Li, Dag Tjøstheim, Jiti Gao
In this paper, we study parametric nonlinear regression under the Harris recurrent Markov chain framework. We first consider the nonlinear least squares estimators of the parameter…
Model selection and structure specification in ultra-high dimensional generalised semi-varying coefficient models
Degui Li, Yuan Ke, Wenyang Zhang
In this paper, we study the model selection and structure specification for the generalised semi-varying coefficient models (GSVCMs), where the number of potential covariates is al…
Semiparametric GEE analysis in partially linear single-index models for longitudinal data
Jia Chen, Degui Li, Hua Liang +1
In this article, we study a partially linear single-index model for longitudinal data under a general framework which includes both the sparse and dense longitudinal data cases. A…
Estimation in semi-parametric regression with non-stationary regressors
Jia Chen, Jiti Gao, Degui Li
In this paper, we consider a partially linear model of the form , , where is a null recurrent Markov chain, is a sequenc…