From the 1 of 7 linked papers with an AI index.
6 papers · 1 filter
Bias Correction of Long-memory Estimator of Functional Time Series via the Prefiltered Sieve Bootstrap
Chang Liu, Han Lin Shang
The paper proposes a bias‑correction method using a prefiltered sieve bootstrap to improve estimation of the long‑memory parameter in stationary or nonstationary fractionally integ…
AR-sieve Bootstrap for High-dimensional Time Series
Daning Bi, Han Lin Shang, Yanrong Yang +1
This paper proposes a new AR-sieve bootstrap approach to high-dimensional time series. The major challenge of classical bootstrap methods on high-dimensional time series is two-fol…
Robust Functional Logistic Regression
Berkay Akturk, Ufuk Beyaztas, Han Lin Shang
Functional logistic regression is a popular model to capture a linear relationship between binary response and functional predictor variables. However, many methods used for parame…
Robust function-on-function interaction regression
Ufuk Beyaztas, Han Lin Shang, Abhijit Mandal
A function-on-function regression model with quadratic and interaction effects of the covariates provides a more flexible model. Despite several attempts to estimate the model's pa…
Forecasting high-dimensional functional time series with dual-factor structures
Chen Tang, Han Lin Shang, Yanrong Yang +1
We propose a dual-factor model for high-dimensional functional time series (HDFTS) that considers multiple populations. The HDFTS is first decomposed into a collection of functiona…
Forecasting high-dimensional functional time series: Application to sub-national age-specific mortality
Cristian F. Jiménez-Varón, Ying Sun, Han Lin Shang
We study the modeling and forecasting of high-dimensional functional time series (HDFTS), which can be cross-sectionally correlated and temporally dependent. We introduce a decompo…