From the 1 of 14 linked papers with an AI index.
9 papers · 1 filter
Interpretable models for forecasting high-dimensional functional time series
Han Lin Shang, Cristian F. Jiménez-Varón
The paper proposes an interpretable framework for modeling and forecasting high‑dimensional functional time series by separating a deterministic mean component via functional ANOVA…
Visualizing and forecasting subnational life-table death counts: Gap forecasting methods
Han Lin Shang, Andrea Nigri
Subnational life-table death counts are highly correlated across time and space and differ by gender. While these associations are helpful in improving forecasts through joint mode…
Modeling and forecasting subnational age distribution of death counts
Han Lin Shang, Cristian F. Jiménez-Varón
Existing mortality forecasting methods focus on age-specific mortality rates, which lie in an unconstrained space and overlook the distributional nature of life-table death counts.…
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,…
Attribution of Spurious Factors from High-Dimensional Functional Time Series
Adam Nie, Yanrong Yang, Han Lin Shang +1
This article explores a general factor structure for high-dimensional nonstationary functional time series, encompassing a wide range of factor models studied in the existing liter…
Conformal prediction for high-dimensional functional time series: Applications to subnational mortality
Han Lin Shang
In statistics, forecast uncertainty is often quantified using a specified statistical model, though such approaches may be vulnerable to model misspecification, selection bias, and…