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Han Lin Shang
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2020 – today
- 2023
- [j24]Antonio Elías
, Raúl Jiménez, Han Lin Shang
:
Depth-based reconstruction method for incomplete functional data. Comput. Stat. 38(3): 1507-1535 (2023) - [j23]Ufuk Beyaztas
, Han Lin Shang
:
Robust Functional Linear Regression Models. R J. 15(1): 212-233 (2023) - 2022
- [j22]Ufuk Beyaztas
, Han Lin Shang
, Abdel-Salam G. Abdel-Salam
:
Functional linear models for interval-valued data. Commun. Stat. Simul. Comput. 51(7): 3513-3532 (2022) - [j21]Ufuk Beyaztas
, Han Lin Shang
:
A comparison of parameter estimation in function-on-function regression. Commun. Stat. Simul. Comput. 51(8): 4607-4637 (2022) - [j20]Yang Yang
, Yanrong Yang
, Han Lin Shang
:
Feature extraction for functional time series: Theory and application to NIR spectroscopy data. J. Multivar. Anal. 189: 104863 (2022) - [j19]Antonio Elías
, Raúl Jiménez
, Han Lin Shang
:
On projection methods for functional time series forecasting. J. Multivar. Anal. 189: 104890 (2022) - [j18]Ufuk Beyaztas
, Han Lin Shang
:
Function-on-function linear quantile Regression. Math. Model. Anal. 27(2): 322-341 (2022) - [j17]Giles Hooker
, Han Lin Shang
:
Selecting the derivative of a functional covariate in scalar-on-function regression. Stat. Comput. 32(3): 35 (2022) - 2021
- [j16]Ufuk Beyaztas
, Han Lin Shang
:
A partial least squares approach for function-on-function interaction regression. Comput. Stat. 36(2): 911-939 (2021) - 2020
- [j15]Han Lin Shang
:
Estimation of a functional single index model with dependent errors and unknown error density. Commun. Stat. Simul. Comput. 49(12): 3111-3133 (2020)
2010 – 2019
- 2019
- [j14]Han Lin Shang
, Yang Yang
, Fearghal Kearney
:
Intraday forecasts of a volatility index: functional time series methods with dynamic updating. Ann. Oper. Res. 282(1-2): 331-354 (2019) - [j13]Yuan Gao
, Han Lin Shang
, Yanrong Yang:
High-dimensional functional time series forecasting: An application to age-specific mortality rates. J. Multivar. Anal. 170: 232-243 (2019) - 2018
- [j12]Han Lin Shang
:
Bootstrap methods for stationary functional time series. Stat. Comput. 28(1): 1-10 (2018) - 2017
- [j11]Piotr Kokoszka, Gregory Rice, Han Lin Shang
:
Inference for the autocovariance of a functional time series under conditional heteroscedasticity. J. Multivar. Anal. 162: 32-50 (2017) - 2016
- [j10]Han Lin Shang
:
A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data. J. Multivar. Anal. 146: 95-104 (2016) - 2015
- [j9]Han Lin Shang
:
Resampling Techniques for Estimating the Distribution of Descriptive Statistics of Functional Data. Commun. Stat. Simul. Comput. 44(3): 614-635 (2015) - 2014
- [j8]Xibin Zhang, Maxwell L. King, Han Lin Shang
:
A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density. Comput. Stat. Data Anal. 78: 218-234 (2014) - [j7]Han Lin Shang
:
Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density. Comput. Stat. 29(3): 829-848 (2014) - 2013
- [j6]Han Lin Shang
:
Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density. Comput. Stat. Data Anal. 67: 185-198 (2013) - [j5]Han Lin Shang:
ftsa: An R Package for Analyzing Functional Time Series. R J. 5(1): 64 (2013) - 2011
- [j4]Rob J. Hyndman
, Roman A. Ahmed, George Athanasopoulos
, Han Lin Shang
:
Optimal combination forecasts for hierarchical time series. Comput. Stat. Data Anal. 55(9): 2579-2589 (2011) - [j3]Han Lin Shang
, Rob J. Hyndman
:
Nonparametric time series forecasting with dynamic updating. Math. Comput. Simul. 81(7): 1310-1324 (2011) - [j2]Han Lin Shang:
rainbow: An R Package for Visualizing Functional Time Series. R J. 3(2): 54 (2011)
2000 – 2009
- 2009
- [j1]Han Lin Shang:
D. Hand: Information generation (2007): how data rule our world. Comput. Stat. 24(2): 373-374 (2009)
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