Grouped multivariate functional time series method: An application to mortality forecasting

Han Lin Shang*, Yang Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Age-specific mortality rates are often disaggregated by different attributes, such as sex and state. Forecasting age-specific mortality rates at the sub-national levels may not add up to the forecasts at the national level. Further, the independent forecasts may not utilize correlation among sub-populations to improve forecast accuracy. Using Japanese mortality data, we extend the grouped univariate functional time series methods to grouped multivariate functional time series forecasting methods.
Original languageEnglish
Title of host publicationFunctional statistics and related fields
EditorsGermán Aneiros, Enea G. Bongiorno, Ricardo Cao, Philippe Vieu
Place of PublicationCham
PublisherSpringer
Chapter31
Pages233-241
Number of pages9
ISBN (Electronic)9783319558462
ISBN (Print)9783319558455
DOIs
Publication statusPublished - 2017
Externally publishedYes
EventInternational Workshop on Functional and Operatorial Statistics (4th : 2017) - La Coruña, Spain
Duration: 15 Jun 201717 Jun 2017

Publication series

NameContributions to statistics
PublisherSpringer

Conference

ConferenceInternational Workshop on Functional and Operatorial Statistics (4th : 2017)
CountrySpain
CityLa Coruña
Period15/06/1717/06/17

Keywords

  • Forecast Horizon
  • Aggregation Constraint
  • Point Forecast
  • Functional Principal Component
  • Holdout Sample

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