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Grouped multivariate functional time series method: An application to mortality forecasting, in Functional Statistics and Related Fields

Shang, Hanlin; Yang, Yang

Description

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

dc.contributor.authorShang, Hanlin
dc.contributor.authorYang, Yang
dc.contributor.editorAneiros, Germán
dc.contributor.editorBongiorno, Enea G.
dc.contributor.editorCao, Ricardo
dc.contributor.editorVieu, Philippe
dc.date.accessioned2021-06-30T06:04:58Z
dc.identifier.isbn9783319558455
dc.identifier.urihttp://hdl.handle.net/1885/238467
dc.description.abstractAge-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
dc.format.mimetypeapplication/pdf
dc.language.isoen_AU
dc.publisherSpringer
dc.relation.ispartofFunctional Statistics and Related Fields
dc.relation.isversionof1 Edition
dc.rights© Springer International Publishing AG 2017
dc.titleGrouped multivariate functional time series method: An application to mortality forecasting, in Functional Statistics and Related Fields
dc.typeBook chapter
local.description.notesImported from ARIES
dc.date.issued2017
local.identifier.absfor010401 - Applied Statistics
local.identifier.ariespublicationu1027566xPUB62
local.publisher.urlhttps://link.springer.com/
local.type.statusAccepted Version
local.contributor.affiliationShang, Hanlin, College of Business and Economics, ANU
local.contributor.affiliationYang, Yang, College of Business and Economics, ANU
local.description.embargo2099-12-31
local.bibliographicCitation.startpage233
local.bibliographicCitation.lastpage241
local.identifier.doi10.1007/978-3-319-55846-2_31
local.identifier.absseo970101 - Expanding Knowledge in the Mathematical Sciences
dc.date.updated2020-11-23T10:36:30Z
local.bibliographicCitation.placeofpublicationSpringer, Cham
CollectionsANU Research Publications

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