Han Lin Shang : Citation Profile


Are you Han Lin Shang?

Australian National University

5

H index

3

i10 index

107

Citations

RESEARCH PRODUCTION:

25

Articles

10

Papers

RESEARCH ACTIVITY:

   9 years (2008 - 2017). See details.
   Cites by year: 11
   Journals where Han Lin Shang has often published
   Relations with other researchers
   Recent citing documents: 33.    Total self citations: 16 (13.01 %)

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/psh533
   Updated: 2018-12-08    RAS profile: 2018-04-10    
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Relations with other researchers


Works with:

King, Maxwell (4)

Zhang, Xibin (3)

Authors registered in RePEc who have co-authored more than one work in the last five years with Han Lin Shang.

Is cited by:

Hyndman, Rob (16)

Athanasopoulos, George (5)

López Cabrera, Brenda (4)

Silvestrini, Andrea (3)

Sbrana, Giacomo (3)

Medel, Carlos A. (2)

Cobb, Marcus (2)

Capistrán, Carlos (2)

Nikolopoulos, Konstantinos (2)

Schulz, Franziska (2)

Yazgan, Ege (1)

Cites to:

Hyndman, Rob (69)

Zhang, Xibin (18)

King, Maxwell (16)

Yu, Jun (11)

Lee, Ronald (10)

Li, Qi (6)

Racine, Jeffrey (6)

Athanasopoulos, George (6)

Shephard, Neil (5)

Brooks, Robert (5)

Blake, David (5)

Main data


Where Han Lin Shang has published?


Journals with more than one article published# docs
Journal of Applied Statistics6
Computational Statistics & Data Analysis3
Demographic Research2

Working Papers Series with more than one paper published# docs
Monash Econometrics and Business Statistics Working Papers / Monash University, Department of Econometrics and Business Statistics10

Recent works citing Han Lin Shang (2018 and 2017)


YearTitle of citing document
2017Cohort effects in mortality modelling: a Bayesian state-space approach. (2017). Fung, Man Chung ; Shevchenko, Pavel V ; Peters, Gareth W. In: Papers. RePEc:arx:papers:1703.08282.

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2018Aggregated moving functional median in robust prediction of hierarchical functional time series - an application to forecasting web portal users behaviors. (2018). Kosiorowski, Daniel ; Rydlewski, Jerzy P ; Mielczarek, Dominik. In: Papers. RePEc:arx:papers:1710.02669.

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2017Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for Day and Night Air Pollution in Silesia Region: A Critical Overview. (2017). Kosiorowski, Daniel ; Rydlewski, Jerzy P ; Mielczarek, Dominik. In: Papers. RePEc:arx:papers:1712.03797.

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2017Prediction Bands for Functional Data Based on Depth Measures. (2017). Fernandez, Antonio Elias ; Jimenez, Raul Jose . In: DES - Working Papers. Statistics and Econometrics. WS. RePEc:cte:wsrepe:24606.

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2017Depth-based nonparametric description of functional data, with emphasis on use of spatial depth. (2017). Serfling, Robert ; Wijesuriya, Uditha . In: Computational Statistics & Data Analysis. RePEc:eee:csdana:v:105:y:2017:i:c:p:24-45.

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2017Application of wavelet decomposition in time-series forecasting. (2017). Yazgan, Ege ; Genay, Ramazan ; Zhang, Keyi . In: Economics Letters. RePEc:eee:ecolet:v:158:y:2017:i:c:p:41-46.

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2017Functional time series forecasting with dynamic updating: An application to intraday particulate matter concentration. (2017). Shang, Han Lin . In: Econometrics and Statistics. RePEc:eee:ecosta:v:1:y:2017:i:c:p:184-200.

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2017Forecasting with temporal hierarchies. (2017). Hyndman, Rob ; Athanasopoulos, George ; Petropoulos, Fotios ; Kourentzes, Nikolaos. In: European Journal of Operational Research. RePEc:eee:ejores:v:262:y:2017:i:1:p:60-74.

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2017Integrated hierarchical forecasting. (2017). , Clint ; van Dalen, Jan . In: European Journal of Operational Research. RePEc:eee:ejores:v:263:y:2017:i:2:p:412-418.

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2018The impact of special days in call arrivals forecasting: A neural network approach to modelling special days. (2018). Kourentzes, Nikolaos ; Barrow, Devon. In: European Journal of Operational Research. RePEc:eee:ejores:v:264:y:2018:i:3:p:967-977.

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2018A greedy aggregation–decomposition method for intermittent demand forecasting in fashion retailing. (2018). Li, Chongshou ; Lim, Andrew. In: European Journal of Operational Research. RePEc:eee:ejores:v:269:y:2018:i:3:p:860-869.

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2018A bottom-up methodology for long term electricity consumption forecasting of an industrial sector - Application to pulp and paper sector in Brazil. (2018). , Felipe ; Calili, Rodrigo F ; Lourenco, Plutarcho M ; Cyrino, Fernando L ; Souza, Reinaldo C. In: Energy. RePEc:eee:energy:v:144:y:2018:i:c:p:1107-1118.

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2017Forecasting compositional time series: A state space approach. (2017). Snyder, Ralph ; Ord, Keith ; McLaren, Keith ; Beaumont, Adrian N ; Koehler, Anne B. In: International Journal of Forecasting. RePEc:eee:intfor:v:33:y:2017:i:2:p:502-512.

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2017Robust estimators in semi-functional partial linear regression models. (2017). Vahnovan, Alejandra ; Boente, Graciela. In: Journal of Multivariate Analysis. RePEc:eee:jmvana:v:154:y:2017:i:c:p:59-84.

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2017Investigating the added value of integrating human judgement into statistical demand forecasting systems. (2017). Baecke, Philippe ; Vanderheyden, Karlien ; de Baets, Shari . In: International Journal of Production Economics. RePEc:eee:proeco:v:191:y:2017:i:c:p:85-96.

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2017Assessing CO2 emissions in Chinas iron and steel industry: A nonparametric additive regression approach. (2017). Lin, Boqiang ; Xu, Bin. In: Renewable and Sustainable Energy Reviews. RePEc:eee:rensus:v:72:y:2017:i:c:p:325-337.

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2017Asymptotic properties of principal component projections with repeated eigenvalues. (2017). Petrovich, Justin ; Reimherr, Matthew. In: Statistics & Probability Letters. RePEc:eee:stapro:v:130:y:2017:i:c:p:42-48.

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2018On dimension reduction models for functional data. (2018). Vieu, Philippe . In: Statistics & Probability Letters. RePEc:eee:stapro:v:136:y:2018:i:c:p:134-138.

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2018Optimal weighting schemes for longitudinal and functional data. (2018). Zhang, Xiaoke ; Wang, Jane-Ling. In: Statistics & Probability Letters. RePEc:eee:stapro:v:138:y:2018:i:c:p:165-170.

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2018On reconciling macro and micro energy transport forecasts for strategic decision making in the tanker industry. (2018). Abouarghoub, Wessam ; Petropoulos, Fotios ; Nomikos, Nikos K. In: Transportation Research Part E: Logistics and Transportation Review. RePEc:eee:transe:v:113:y:2018:i:c:p:225-238.

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2017Twenty-Two Years of Inflation Assessment and Forecasting Experience at the Bulletin of EU & US Inflation and Macroeconomic Analysis. (2017). Espasa, Antoni ; Senra, Eva . In: Econometrics. RePEc:gam:jecnmx:v:5:y:2017:i:4:p:44-:d:114224.

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2017Evaluating Extensions to Coherent Mortality Forecasting Models. (2017). Shair, Syazreen ; Parr, Nick ; Purcal, Sachi . In: Risks. RePEc:gam:jrisks:v:5:y:2017:i:1:p:16-:d:92753.

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2017Stochastic Period and Cohort Effect State-Space Mortality Models Incorporating Demographic Factors via Probabilistic Robust Principal Components. (2017). Toczydlowska, Dorota ; Shevchenko, Pavel V ; Fung, Man Chung ; Peters, Gareth W. In: Risks. RePEc:gam:jrisks:v:5:y:2017:i:3:p:42-:d:106077.

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2018Special Issue “Ageing Population Risks”. (2018). Shevchenko, Pavel V. In: Risks. RePEc:gam:jrisks:v:6:y:2018:i:1:p:16-:d:134739.

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2018An Empirical Study on Stochastic Mortality Modelling under the Age-Period-Cohort Framework: The Case of Greece with Applications to Insurance Pricing. (2018). Bozikas, Apostolos ; Pitselis, Georgios . In: Risks. RePEc:gam:jrisks:v:6:y:2018:i:2:p:44-:d:142754.

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2017Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization. (2017). Hyndman, Rob ; Athanasopoulos, George ; Wickramasuriya, Shanika L. In: Monash Econometrics and Business Statistics Working Papers. RePEc:msh:ebswps:2017-22.

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2017Coherent Probabilistic Forecasts for Hierarchical Time Series. (2017). Hyndman, Rob ; Taylor, James W ; Ben Taieb, Souhaib . In: Monash Econometrics and Business Statistics Working Papers. RePEc:msh:ebswps:2017-3.

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2018Probabilisitic forecasts in hierarchical time series. (2018). Hyndman, Rob ; Athanasopoulos, George ; Panagiotelis, Anastasios ; Gamakumara, Puwasala. In: Monash Econometrics and Business Statistics Working Papers. RePEc:msh:ebswps:2018-11.

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2017Joint Forecast Combination of Macroeconomic Aggregates and Their Components. (2017). Cobb, Marcus. In: MPRA Paper. RePEc:pra:mprapa:76556.

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2018Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach. (2018). Cobb, Marcus. In: MPRA Paper. RePEc:pra:mprapa:88593.

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2019Retail forecasting: research and practice. (2019). Fildes, Robert ; Kolassa, Stephan ; Ma, Shaohui . In: MPRA Paper. RePEc:pra:mprapa:89356.

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2017Lifespan Disparity as an Additional Indicator for Evaluating Mortality Forecasts. (2017). Bohk-Ewald, Christina ; Rau, Roland ; Ebeling, Marcus . In: Demography. RePEc:spr:demogr:v:54:y:2017:i:4:d:10.1007_s13524-017-0584-0.

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2017Uniform in bandwidth consistency for various kernel estimators involving functional data. (2017). Kara-Zaitri, Lydia ; Vieu, Philippe ; Rachdi, Mustapha ; Laksaci, Ali. In: Journal of Nonparametric Statistics. RePEc:taf:gnstxx:v:29:y:2017:i:1:p:85-107.

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Works by Han Lin Shang:


YearTitleTypeCited
2017Methods for Scalar-on-Function Regression In: International Statistical Review.
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article2
2017A Plug-in Bandwidth Selection Procedure for Long-Run Covariance Estimation with Stationary Functional Time Series In: Journal of Time Series Analysis.
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article0
2011Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods In: Demographic Research.
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article17
2012Point and interval forecasts of age-specific life expectancies In: Demographic Research.
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article1
2011Optimal combination forecasts for hierarchical time series In: Computational Statistics & Data Analysis.
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article39
2013Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density In: Computational Statistics & Data Analysis.
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article2
2014A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density In: Computational Statistics & Data Analysis.
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article1
2013A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density.(2013) In: Monash Econometrics and Business Statistics Working Papers.
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This paper has another version. Agregated cites: 1
paper
2017Grouped multivariate and functional time series forecasting:An application to annuity pricing In: Insurance: Mathematics and Economics.
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article2
2016A multilevel functional data method for forecasting population, with an application to the United Kingdom In: International Journal of Forecasting.
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article0
2016A Bayesian approach for determining the optimal semi-metric and bandwidth in scalar-on-function quantile regression with unknown error density and dependent functional data In: Journal of Multivariate Analysis.
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article0
2011Nonparametric time series forecasting with dynamic updating In: Mathematics and Computers in Simulation (MATCOM).
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article3
2009Nonparametric time series forecasting with dynamic updating.(2009) In: Monash Econometrics and Business Statistics Working Papers.
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paper
2016Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors In: Econometrics.
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article2
2013Bayesian bandwidth selection for a nonparametric regession model with mixed types of regressors.(2013) In: Monash Econometrics and Business Statistics Working Papers.
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paper
2017Multivariate Functional Time Series Forecasting: Application to Age-Specific Mortality Rates In: Risks.
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article2
2017Reconciling Forecasts of Infant Mortality Rates at National and Sub-National Levels: Grouped Time-Series Methods In: Population Research and Policy Review.
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article0
2008Rainbow plots, Bagplots and Boxplots for Functional Data In: Monash Econometrics and Business Statistics Working Papers.
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paper15
2010Nonparametric modeling and forecasting electricity demand: an empirical study In: Monash Econometrics and Business Statistics Working Papers.
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paper0
2010A comparison of ten principal component methods for forecasting mortality rates In: Monash Econometrics and Business Statistics Working Papers.
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paper2
2011Bayesian estimation of bandwidths for a nonparametric regression model with a flexible error density In: Monash Econometrics and Business Statistics Working Papers.
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paper0
2011A survey of functional principal component analysis In: Monash Econometrics and Business Statistics Working Papers.
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paper5
2014A survey of functional principal component analysis.(2014) In: AStA Advances in Statistical Analysis.
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article
2012Point and interval forecasts of age-specific fertility rates: a comparison of functional principal component methods In: Monash Econometrics and Business Statistics Working Papers.
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paper0
2016Grouped functional time series forecasting: An application to age-specific mortality rates In: Monash Econometrics and Business Statistics Working Papers.
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paper2
2014Bayesian bandwidth estimation for a semi-functional partial linear regression model with unknown error density In: Computational Statistics.
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article2
2014Bayesian bandwidth estimation for a functional nonparametric regression model with mixed types of regressors and unknown error density In: Journal of Nonparametric Statistics.
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article5
2011Dynamic linear models with R In: Journal of Applied Statistics.
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article0
2011Bayesian Nonparametrics In: Journal of Applied Statistics.
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article0
2011Non-Parametric Econometrics In: Journal of Applied Statistics.
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article0
2012Graphics for statistics and data analysis with R In: Journal of Applied Statistics.
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article0
2013The BUGS book: a practical introduction to Bayesian analysis In: Journal of Applied Statistics.
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article0
2013Functional time series approach for forecasting very short-term electricity demand In: Journal of Applied Statistics.
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article4
2015Statistically tested comparisons of the accuracy of forecasting methods for age-specific and sex-specific mortality and life expectancy In: Population Studies.
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article1
2017Forecasting intraday S&P 500 index returns: A functional time series approach In: Journal of Forecasting.
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article0

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