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Han Lin Shang
Macquarie University
StatisticsEconometricsTime seriesMathematicsFunctional principal component analysis
102Publications
14H-index
951Citations
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Publications 84
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#1Han Lin Shang (Macquarie University)H-Index: 14
Last. Yang Yang
view all 2 authors...
When modeling sub-national mortality rates, it is important to incorporate any possible correlation among sub-populations to improve forecast accuracy. Moreover, forecasts at the sub-national level should aggregate consistently across the forecasts at the national level. In this study, we apply a grouped multivariate functional time series to forecast Australian regional and remote age-specific mortality rates and reconcile forecasts in a group structure using various methods. Our proposed metho...
#1Han Lin Shang (Macquarie University)H-Index: 14
#2Steven Haberman (Lond: University of London)H-Index: 32
An essential input of annuity pricing is the future retiree mortality. From observed age-specific mortality data, modeling and forecasting can be taken place in two routes. On the one hand, we can first truncate the available data to retiree ages and then produce mortality forecasts based on a partial age-range model. On the other hand, with all available data, we can first apply a full age-range model to produce forecasts and then truncate the mortality forecasts to retiree ages. We investigate...
#1Han Lin ShangH-Index: 14
#2Steven Haberman (Lond: University of London)H-Index: 32
An essential input of annuity pricing is the future retiree mortality. From observed age-specific mortality data, modeling and forecasting can be taken place in two routes. On the one hand, we can first truncate the available data to retiree ages and then produce mortality forecasts based on a partial age-range model. On the other hand, with all available data, we can first apply a full age-range model to produce forecasts and then truncate the mortality forecasts to retiree ages. We investigate...
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#1Han Lin Shang (ANU: Australian National University)H-Index: 14
AbstractWhen generating social policies and pricing annuity at national and subnational levels, it is essential both to forecast mortality accurately and ensure that forecasts at the subnational le...
2 CitationsSource
#1Ufuk Beyaztas (Bartın University)H-Index: 4
#2Han Lin Shang (Macquarie University)H-Index: 14
Recent technological developments have enabled us to collect complex and high-dimensional data in many scientific fields, such as population health, meteorology, econometrics, geology, and psycholo...
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#1Degui Li (Ebor: University of York)H-Index: 14
#2Peter Robinson (LSE: London School of Economics and Political Science)H-Index: 66
Last. Han Lin Shang (ANU: Australian National University)H-Index: 14
view all 3 authors...
AbstractWe introduce methods and theory for functional or curve time series with long-range dependence. The temporal sum of the curve process is shown to be asymptotically normally distributed, the...
7 CitationsSource
#1Ufuk Beyaztas (Bartın University)H-Index: 4
#2Han Lin Shang (Macquarie University)H-Index: 14
Recent technological developments have enabled us to collect complex and high-dimensional data in many scientific fields, such as population health, meteorology, econometrics, geology, and psychology. It is common to encounter such datasets collected repeatedly over a continuum. Functional data, whose sample elements are functions in the graphical forms of curves, images, and shapes, characterize these data types. Functional data analysis techniques reduce the complex structure of these data and...
ABSTRACTThis study examines the optimal selections of bandwidth and semi-metric for a functional partial linear model. Our proposed method begins by estimating the unknown error density using a ker...
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#1Han Lin Shang (ANU: Australian National University)H-Index: 14
#2Steven Haberman (Lond: University of London)H-Index: 32
We consider a compositional data analysis approach to forecasting the age distribution of death counts. Using the age-specific period life-table death counts in Australia obtained from the Human Mortality Database, the compositional data analysis approach produces more accurate one- to 20-step-ahead point and interval forecasts than Lee-Carter method, Hyndman-Ullah method, and two na¨ive random walk methods. The improved forecast accuracy of period life-table death counts is of great interest to...
1 CitationsSource
This study examines the optimal selections of bandwidth and semi-metric for a functional partial linear model. Our proposed method begins by estimating the unknown error density using a kernel density estimator of residuals, where the regression function, consisting of parametric and nonparametric components, can be estimated by functional principal component and functional Nadayara-Watson estimators. The estimation accuracy of the regression function and error density crucially depends on the o...
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