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Multi-population modelling and forecasting life-table death counts

Shang, Han Lin; Haberman, Steven; Xu, Ruofan - In: Insurance / Mathematics & economics 106 (2022), pp. 239-253

Persistent link: https://www.econbiz.de/10013380527

Weighted compositional functional data analysis for modeling and forecasting life-table death counts

Shang, Han Lin; Haberman, Steven - In: Journal of forecasting 43 (2024) 8, pp. 3051-3071

Persistent link: https://www.econbiz.de/10015110599

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

Shang, Han Lin - In: Scandinavian actuarial journal 2020 (2020) 4, pp. 307-322

Persistent link: https://www.econbiz.de/10012262738

Forecasting intraday S&P 500 index returns : a functional time series approach

Shang, Han Lin - In: Journal of forecasting 36 (2017) 7, pp. 741-755

Persistent link: https://www.econbiz.de/10011860709

A comparison of hurst exponent estimators in long-range dependent curve time series

Shang, Han Lin - In: Journal of time series econometrics 12 (2020) 1, pp. 1-39

Persistent link: https://www.econbiz.de/10012258318

Forecasting intraday financial time series with sieve bootstrapping and dynamic updating

Shang, Han Lin; Ji, Kaiying - In: Journal of forecasting 42 (2023) 8, pp. 1973-1988

Persistent link: https://www.econbiz.de/10014432826

Bayesian bandwidth selection for a nonparametric regression model with mixed types of regressors

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - 2013

Persistent link: https://www.econbiz.de/10009775496

A sampling algorithm for bandwidth estimation in a nonparametric regression model with a flexible error density

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - 2013

Persistent link: https://www.econbiz.de/10010189540

Bayesian bandwidth selection for a nonparametric regression model with mixed types of regressors

Zhang, Xibin; King, Maxwell L.; Shang, Han Lin - In: Econometrics : open access journal 4 (2016) 2, pp. 1-27

This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density. The error density is approximated by the kernel density estimator of the unobserved errors, while the regression function...

Persistent link: https://www.econbiz.de/10011506243

Dynamic principal component regression : application to age-specific mortality forecasting

Shang, Han Lin - In: Astin bulletin : the journal of the International … 49 (2019) 3, pp. 619-645

Persistent link: https://www.econbiz.de/10012116374