2 citations · 3 across the 24 of their papers we have counts for
27 papers
Age-specific demographic modeling and forecasting: Rolling window, expanding window, or both?
Sizhe Chen, Han Lin Shang
Rolling and expanding windows are widely used in age-specific demographic modeling and forecasting. Building on these approaches, we propose a simple combination method that assign…
Conformal prediction for functional time series: Application to age-specific mortality rates
Han Lin Shang
In demographic literature, forecast uncertainty is often quantified with a statistical model. This model-based approach may potentially suffer from drawbacks, namely model misspeci…
Robust spatial scalar-on-function regression: A Fisher-consistent redescending M-estimation approach
Muge Mutis, Ufuk Beyaztas, Han Lin Shang
We develop a Fisher-consistent redescending robust estimator for the spatial scalar-on-function regression model, where a scalar response depends on both a functional predictor and…
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…
Penalized spatial function-on-function regression
Ufuk Beyaztas, Han Lin Shang, Gizel Bakicierler Sezer
The function-on-function regression model is fundamental for analyzing relationships between functional covariates and responses. However, most existing function-on-function regres…
Mortality Models Ensemble via Shapley Value
Giovanna Bimonte, Maria Russolillo, Han Lin Shang +1
Model averaging techniques in the actuarial literature aim to forecast future longevity appropriately by combining forecasts derived from various models. This approach often yields…
Spatial Scalar-on-Function Quantile Regression Model
Muge Mutis, Ufuk Beyaztas, Filiz Karaman +1
This paper introduces a novel spatial scalar-on-function quantile regression model that extends classical scalar-on-function models to account for spatial dependence and heterogene…
Age-period modeling of mortality gaps: the cases of cancer and circulatory diseases
Giacomo Lanfiuti Baldi, Andrea Nigri, Han Lin Shang
Understanding and modeling mortality patterns, especially differences in mortality rates between populations, is vital for demographic analysis and public health planning. We compa…
Extending finite mixture models with skew-normal distributions and hidden Markov models for time series
Andrea Nigri, Marco Forti, Han Lin Shang
We introduce an extension of finite mixture models by incorporating skew-normal distributions within a Hidden Markov Model framework. By assuming a constant transition probability…
Stock Return Prediction based on a Functional Capital Asset Pricing Model
Ufuk Beyaztas, Kaiying Ji, Han Lin Shang +1
The capital asset pricing model (CAPM) is readily used to capture a linear relationship between the daily returns of an asset and a market index. We extend this model to an intrada…
Penalized function-on-function linear quantile regression
Ufuk Beyaztas, Han Lin Shang, Semanur Saricam
We introduce a novel function-on-function linear quantile regression model to characterize the entire conditional distribution of a functional response for a given functional predi…
Testing for integer integration in functional time series
Won-Ki Seo, Han Lin Shang
We develop a statistical testing procedure to examine whether the curve-valued time series of interest is integrated of order d for an integer d. The proposed procedure can disting…
Change-point detection in functional time series: Applications to age-specific mortality and fertility
Han Lin Shang
We consider determining change points in a time series of age-specific mortality and fertility curves observed over time. We propose two detection methods for identifying these cha…
Enhancing Spatial Functional Linear Regression with Robust Dimension Reduction Methods
Ufuk Beyaztas, Abhijit Mandal, Han Lin Shang
This paper introduces a robust estimation strategy for the spatial functional linear regression model using dimension reduction methods, specifically functional principal component…
Uncertainty Learning for High-dimensional Mean-variance Portfolio
Ruike Wu, Yanrong Yang, Han Lin Shang +1
Robust estimation for modern portfolio selection on a large set of assets becomes more important due to large deviation of empirical inference on big data. We propose a distributio…
Dependence-based fuzzy clustering of functional time series
Angel Lopez-Oriona, Ying Sun, Han Lin Shang
Time series clustering is essential in scientific applications, yet methods for functional time series, collections of infinite-dimensional curves treated as random elements in a H…
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…
Is the age pension in Australia sustainable and fair? Evidence from forecasting the old-age dependency ratio using the Hamilton-Perry model
Sizhe Chen, Han Lin Shang, Yang Yang
The age pension aims to assist eligible elderly Australians meet specific age and residency criteria in maintaining basic living standards. In designing efficient pension systems,…
Forecasting intraday financial time series with sieve bootstrapping and dynamic updating
Han Lin Shang, Kaiying Ji
Intraday financial data often take the form of a collection of curves that can be observed sequentially over time, such as intraday stock price curves. These curves can be viewed a…
Stopping time detection of wood panel compression: A functional time series approach
H. L. Shang, J. Cao, P. Sang
We consider determining the optimal stopping time for the glue curing of wood panels in an automatic process environment. Using the near-infrared spectroscopy technology to monitor…
Factor-augmented model for functional data
Yuan Gao, Han Lin Shang, Yanrong Yang
We propose modeling raw functional data as a mixture of a smooth function and a high-dimensional factor component. The conventional approach to retrieving the smooth function from…
A model sufficiency test using permutation entropy
Xin Huang, Han Lin Shang, David Pitt
Using the ordinal pattern concept in permutation entropy, we propose a model sufficiency test to study a given model's point prediction accuracy. Compared to some classical model s…
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…
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…