b'Han Lin Shang'

Functional time series forecasting of extreme values

We consider forecasting functional time series of extreme values within ...
12/19/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
A partial least squares approach for function-on-function interaction regression

A partial least squares regression is proposed for estimating the functi...
12/09/2020 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
Change point detection for COVID-19 excess deaths in Belgium

Emerging at the end of 2019, COVID-19 has become a public health threat ...
11/16/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models

The bootstrap procedure has emerged as a general framework to construct ...
11/16/2020 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
Bayesian bandwidth estimation for local linear fitting in nonparametric regression models

This paper presents a Bayesian sampling approach to bandwidth estimation...
11/09/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Granger causality of bivariate stationary curve time series

We study causality between bivariate curve time series using the Granger...
10/11/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Synergy in fertility forecasting: Improving forecast accuracy through model averaging

Accuracy in fertility forecasting has proved challenging and warrants re...
08/19/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Forecasting Australian subnational age-specific mortality rates

When modeling sub-national mortality rates, it is important to incorpora...
07/07/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Retiree mortality forecasting: A partial age-range or a full age-range model?

An essential input of annuity pricing is the future retiree mortality. F...
06/25/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Bootstrap Prediction Bands for Functional Time Series

A bootstrap procedure for constructing pointwise or simultaneous predict...
04/08/2020 ∙ by Efstathios Paparoditis, et al. ∙ 0 ∙ share

read it
A comparison of Hurst exponent estimators in long-range dependent curve time series

The Hurst exponent is the simplest numerical summary of self-similar lon...
03/17/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
A comparison of parameter estimation in function-on-function regression

Recent technological developments have enabled us to collect complex and...
03/12/2020 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
Bayesian bandwidth estimation and semi-metric selection for a functional partial linear model with unknown error density

This study examines the optimal selections of bandwidth and semi-metric ...
02/24/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Forecasting multiple functional time series in a group structure: an application to mortality

When modeling sub-national mortality rates, we should consider three fea...
01/10/2020 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Functional linear models for interval-valued data

Aggregation of large databases in a specific format is a frequently used...
01/08/2020 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
On function-on-function regression: Partial least squares approach

Functional data analysis tools, such as function-on-function regression ...
12/15/2019 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
Implied volatility surface predictability: the case of commodity markets

Recent literature seek to forecast implied volatility derived from equit...
09/21/2019 ∙ by Fearghal Kearney, et al. ∙ 0 ∙ share

read it
Dynamic principal component regression for forecasting functional time series in a group structure

When generating social policies and pricing annuity at national and subn...
09/01/2019 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Forecasting age distribution of death counts: An application to annuity pricing

We consider a compositional data analysis approach to forecasting the ag...
08/05/2019 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Forecasting functional time series using weighted likelihood methodology

Functional time series whose sample elements are recorded sequentially o...
08/01/2019 ∙ by Ufuk Beyaztas, et al. ∙ 0 ∙ share

read it
Dynamic principal component regression: Application to age-specific mortality forecasting

In areas of application, including actuarial science and demography, it ...
05/10/2019 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
A robust functional time series forecasting method

Univariate time series often take the form of a collection of curves obs...
01/17/2019 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Uncovering predictability in the evolution of the WTI oil futures curve

Accurately forecasting the price of oil, the world's most actively trade...
01/08/2019 ∙ by Fearghal Kearney, et al. ∙ 0 ∙ share

read it
Intraday forecasts of a volatility index: Functional time series methods with dynamic updating

As a forward-looking measure of future equity market volatility, the VIX...
11/30/2018 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Estimation of a functional single index model with dependent errors and unknown error density

The problem of error density estimation for a functional single index mo...
10/19/2018 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it
Semiparametric Regression using Variational Approximations

Semiparametric regression offers a flexible framework for modeling non-l...
10/03/2018 ∙ by Francis K. C. Hui, et al. ∙ 0 ∙ share

read it
High-dimensional functional time series forecasting: An application to age-specific mortality rates

We address the problem of forecasting high-dimensional functional time s...
10/02/2018 ∙ by Yuan Gao, et al. ∙ 0 ∙ share

read it
Model confidence sets and forecast combination: An application to age-specific mortality

Model averaging combines forecasts obtained from a range of models, and ...
09/28/2018 ∙ by Han Lin Shang, et al. ∙ 0 ∙ share

read it

Han Lin Shang

Featured Co-authors