38 citations · 86 across the 22 of their papers we have counts for
12 papers · 1 filter
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…
A Beta-GAM Hidden Markov Model for Proportion Time Series
Andrea Nigri, Han Lin Shang, Marco Bonetti
We propose a hidden Markov model for univariate proportion time series taking values in (0,1), where regime switching captures latent structural changes and the emission distributi…
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…
Interpretable models for forecasting high-dimensional functional time series
Han Lin Shang, Cristian F. Jiménez-Varón
We study the modeling and forecasting of high-dimensional functional time series, which can be temporally dependent and cross-sectionally correlated. Central to our implementation…
Constructing prediction intervals for the age distribution of deaths
Han Lin Shang, Steven Haberman
We introduce a model-agnostic procedure to construct prediction intervals for the age distribution of deaths. The age distribution of deaths is an example of constrained data, whic…
Spatial Functional Deep Neural Network Model: A New Prediction Algorithm
Merve Basaran, Ufuk Beyaztas, Han Lin Shang +1
Accurate prediction of spatially dependent functional data is critical for various engineering and scientific applications. In this study, a spatial functional deep neural network…
Spatial function-on-function regression
Ufuk Beyaztas, Han Lin Shang, Gizel Bakicierler Sezer +3
We introduce a spatial function-on-function regression model to capture spatial dependencies in functional data by integrating spatial autoregressive techniques with functional pri…
Nonstationary functional time series forecasting
Han Lin Shang, Yang Yang
We propose a nonstationary functional time series forecasting method with an application to age-specific mortality rates observed over the years. The method begins by taking the fi…
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 density-valued functional panel data
Cristian F. Jiménez-Varón, Ying Sun, Han Lin Shang
We introduce a statistical method for modeling and forecasting functional panel data represented by multiple densities. Density functions are nonnegative and have a constrained int…
Function-on-function linear quantile regression
Ufuk Beyaztas, Han Lin Shang
In this study, we propose a function-on-function linear quantile regression model that allows for more than one functional predictor to establish a more flexible and robust approac…
Bayesian bandwidth estimation for a nonparametric functional regression model with mixed types of regressors and unknown error density
Han Lin Shang
We investigate the issue of bandwidth estimation in a nonparametric functional regression model with function-valued, continuous real-valued and discrete-valued regressors under th…