27 citations · 27 across the 13 of their papers we have counts for
13 papers
Quantifying Long-Range Dependence in Object-Valued Time Series
Won-Ki Seo, Jiazhen Xu, Han Lin Shang
Object-valued time series, including distributions, covariance matrices, networks, and compositions, lack the linear structure required by conventional autocovariance-based definit…
Spherically Embedded Time Series with Unknown Trend and Periodic Components
Jiazhen Xu, Han Lin Shang
Spherically embedded time series are time series with values naturally residing on or can be equivalently mapped to the sphere. Despite their ubiquity in diverse scientific fields,…
Spherical Spatial Autoregressive Model for Spherically Embedded Spatial Data
Jiazhen Xu, Han Lin Shang
Spherically embedded spatial data are spatially indexed observations whose values naturally reside on or can be equivalently mapped to the unit sphere. Such data are increasingly u…
On the Distributed Estimation for Scalar-on-Function Regression Models
Peilun He, Han Lin Shang, Nan Zou
This paper proposes distributed estimation procedures for three scalar-on-function regression models: the functional linear model (FLM), the functional non-parametric model (FNPM),…
White noise testing for functional time series via functional quantile autocorrelation
Ángel López-Oriona, Ying Sun, Hanlin Shang
We introduce a novel class of nonlinear tests for serial dependence in functional time series, grounded in the functional quantile autocorrelation framework. Unlike traditional app…
Forecasting Australian Electricity Generation by Fuel Mix
Han Lin Shang, Lin Han, Stefan Trück
Electricity demand and generation have become increasingly unpredictable with the growing share of variable renewable energy sources in the power system. Forecasting electricity su…
Interpretable additive model for analyzing high-dimensional functional time series
Haixu Wang, Tianyu Guan, Han Lin Shang
High-dimensional functional time series offers a powerful framework for extending functional time series analysis to settings with multiple simultaneous dimensions, capturing both…
Density-valued time series: Nonparametric density-on-density regression
Frédéric Ferraty, Han Lin Shang
This paper is concerned with forecasting probability density functions. Density functions are nonnegative and have a constrained integral; thus, they do not constitute a vector spa…
Intraday FX Volatility-Curve Forecasting with Functional GARCH Approaches
Fearghal Kearney, Han Lin Shang, Yuqian Zhao
This paper seeks to forecast intraday volatility curves for major foreign exchange (FX) currencies using functional GARCH models. Intraday return curves are observed at a daily fre…
A nonlinearity and model specification test for functional time series
Xin Huang, Han Lin Shang, Tak Kuen Siu
An important issue in functional time series analysis is whether an observed series comes from a purely random process. We extend the BDS test, a widely-used nonlinear independence…
Fractionally integrated curve time series with cointegration
Won-Ki Seo, Han Lin Shang
We introduce methods and theory for fractionally cointegrated curve time series. We develop a variance-ratio test to determine the dimensions associated with the nonstationary and…
Forecasting: theory and practice
Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos +77
Forecasting has always been at the forefront of decision making and planning. The uncertainty that surrounds the future is both exciting and challenging, with individuals and organ…
Bootstrap methods for stationary functional time series
Han Lin Shang
Bootstrap methods for estimating the long-run covariance of stationary functional time series are considered. We introduce a versatile bootstrap method that relies on functional pr…