Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method

Han Lin Shang

doi:10.1007/978-81-322-3643-6_9

Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method

Han Lin Shang^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

Abstract

A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers.

Original language	English
Title of host publication	Recent advances in robust statistics
Subtitle of host publication	theory and applications
Editors	Claudio Agostinelli, Ayanendranath Basu, Peter Filzmoser, Diganta Mukherjee
Place of Publication	New Delhi
Publisher	Springer
Pages	169-184
Number of pages	16
ISBN (Electronic)	9788132236436
ISBN (Print)	9788132236412
DOIs	https://doi.org/10.1007/978-81-322-3643-6_9
Publication status	Published - 2016
Externally published	Yes
Event	International Conference on Robust Statistics (ICORS) 2015 - Kolkata, India Duration: 12 Jan 2015 → 16 Jan 2015

Conference

Conference	International Conference on Robust Statistics (ICORS) 2015
Country/Territory	India
City	Kolkata
Period	12/01/15 → 16/01/15

Keywords

Markov Chain Monte Carlo
Forecast Error
Prediction Interval
Forecast Accuracy
Functional Principal Component Analysis

Access to Document

10.1007/978-81-322-3643-6_9

Cite this

@inproceedings{550d0096c01e4ca6ae21c3487ef797e6,

title = "Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method",

abstract = "A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers.",

keywords = "Markov Chain Monte Carlo, Forecast Error, Prediction Interval, Forecast Accuracy, Functional Principal Component Analysis",

author = "Shang, {Han Lin}",

year = "2016",

doi = "10.1007/978-81-322-3643-6_9",

language = "English",

isbn = "9788132236412",

pages = "169--184",

editor = "Claudio Agostinelli and Ayanendranath Basu and Peter Filzmoser and Diganta Mukherjee",

booktitle = "Recent advances in robust statistics",

publisher = "Springer",

note = "International Conference on Robust Statistics (ICORS) 2015 ; Conference date: 12-01-2015 Through 16-01-2015",

}

Shang, HL 2016, Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method. in C Agostinelli, A Basu, P Filzmoser & D Mukherjee (eds), Recent advances in robust statistics: theory and applications. Springer, New Delhi, pp. 169-184, International Conference on Robust Statistics (ICORS) 2015, Kolkata, India, 12/01/15. https://doi.org/10.1007/978-81-322-3643-6_9

Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method. / Shang, Han Lin.
Recent advances in robust statistics: theory and applications. ed. / Claudio Agostinelli; Ayanendranath Basu; Peter Filzmoser; Diganta Mukherjee. New Delhi: Springer, 2016. p. 169-184.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Mortality and life expectancy forecasting for a group of populations in developed countries

T2 - International Conference on Robust Statistics (ICORS) 2015

AU - Shang, Han Lin

PY - 2016

Y1 - 2016

N2 - A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers.

AB - A robust multilevel functional data method is proposed to forecast age-specific mortality rate and life expectancy for two or more populations in developed countries with high-quality vital registration systems. It uses a robust multilevel functional principal component analysis of aggregate and population-specific data to extract the common trend and population-specific residual trend among populations. This method is applied to age- and sex-specific mortality rate and life expectancy for the United Kingdom from 1922 to 2011, and its forecast accuracy is then further compared with standard multilevel functional data method. For forecasting both age-specific mortality and life expectancy, the robust multilevel functional data method produces more accurate point and interval forecasts than the standard multilevel functional data method in the presence of outliers.

KW - Markov Chain Monte Carlo

KW - Forecast Error

KW - Prediction Interval

KW - Forecast Accuracy

KW - Functional Principal Component Analysis

U2 - 10.1007/978-81-322-3643-6_9

DO - 10.1007/978-81-322-3643-6_9

M3 - Conference proceeding contribution

SN - 9788132236412

SP - 169

EP - 184

BT - Recent advances in robust statistics

A2 - Agostinelli, Claudio

A2 - Basu, Ayanendranath

A2 - Filzmoser, Peter

A2 - Mukherjee, Diganta

PB - Springer

CY - New Delhi

Y2 - 12 January 2015 through 16 January 2015

ER -

Mortality and life expectancy forecasting for a group of populations in developed countries: A robust multilevel functional data method

Abstract

Conference

Keywords

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Cite this