Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022)
Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second,...
Gespeichert in:
Veröffentlicht in: | Annals of actuarial science 2023-11, Vol.17 (3), p.643-646 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 646 |
---|---|
container_issue | 3 |
container_start_page | 643 |
container_title | Annals of actuarial science |
container_volume | 17 |
creator | Richards, Stephen J. |
description | Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second, these models can automatically extrapolate mortality rates to ages above the maximum age of the data set. Third, simpler sub-variants of the models exist for forecasting when one of the variables lacks a clear drift. Finally, a minor reparameterisation increases the quality of long-range forecasts of period mortality. |
doi_str_mv | 10.1017/S174849952300012X |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2881259035</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cupid>10_1017_S174849952300012X</cupid><sourcerecordid>2881259035</sourcerecordid><originalsourceid>FETCH-LOGICAL-c326t-c27e9cfcf0941d254c1e07730f2850e9bb1ddc61c44f60c525d2582ac0ae08f33</originalsourceid><addsrcrecordid>eNp1kMFKAzEQhhdRsNQ-gLeAIAquTrJJd3MsRa1Q8NAK3pZsNqmpu5s12R5664Poy_VJTGmhB_E0w8z3__8wUXSJ4R4DTh9mOKUZ5ZyRBAAweT-JertRzADI6aHf7c-jgffLwADlkCW8F9mZrRWStq5V03lkG7TdfI_QRLnadAr5tjKNQqJtnRXyA2nrUG1LVYXxArW2XVWiM0FVW9eJynTr7eYHFWs0F83iDk0NukZzIz8rhW4IEHJ7EZ1pUXk1ONR-9Pb0OB9P4unr88t4NI1lQoZdLEmquNRSA6e4JIxKrCBNE9AkY6B4UeCylEMsKdVDkIywAGVESBAKMp0k_ehq7xsO_1op3-VLu3JNiMxJlmHCOCQsUHhPSWe9d0rnrTO1cOscQ757bf7ntUGD9holbWP8UZGlhHPKMAlIcrAVdeFMuVDH9P-NfwHtqYW2</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2881259035</pqid></control><display><type>article</type><title>Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022)</title><source>Cambridge University Press Journals Complete</source><creator>Richards, Stephen J.</creator><creatorcontrib>Richards, Stephen J.</creatorcontrib><description>Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second, these models can automatically extrapolate mortality rates to ages above the maximum age of the data set. Third, simpler sub-variants of the models exist for forecasting when one of the variables lacks a clear drift. Finally, a minor reparameterisation increases the quality of long-range forecasts of period mortality.</description><identifier>ISSN: 1748-4995</identifier><identifier>EISSN: 1748-5002</identifier><identifier>DOI: 10.1017/S174849952300012X</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Actuarial science ; Age ; Datasets ; Females ; Mortality ; Original Research Paper</subject><ispartof>Annals of actuarial science, 2023-11, Vol.17 (3), p.643-646</ispartof><rights>The Author(s), 2023. Published by Cambridge University Press on behalf of Institute and Faculty of Actuaries</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c326t-c27e9cfcf0941d254c1e07730f2850e9bb1ddc61c44f60c525d2582ac0ae08f33</cites><orcidid>0000-0001-6859-6347</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S174849952300012X/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,776,780,27901,27902,55603</link.rule.ids></links><search><creatorcontrib>Richards, Stephen J.</creatorcontrib><title>Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022)</title><title>Annals of actuarial science</title><addtitle>Ann. actuar. sci</addtitle><description>Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second, these models can automatically extrapolate mortality rates to ages above the maximum age of the data set. Third, simpler sub-variants of the models exist for forecasting when one of the variables lacks a clear drift. Finally, a minor reparameterisation increases the quality of long-range forecasts of period mortality.</description><subject>Actuarial science</subject><subject>Age</subject><subject>Datasets</subject><subject>Females</subject><subject>Mortality</subject><subject>Original Research Paper</subject><issn>1748-4995</issn><issn>1748-5002</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kMFKAzEQhhdRsNQ-gLeAIAquTrJJd3MsRa1Q8NAK3pZsNqmpu5s12R5664Poy_VJTGmhB_E0w8z3__8wUXSJ4R4DTh9mOKUZ5ZyRBAAweT-JertRzADI6aHf7c-jgffLwADlkCW8F9mZrRWStq5V03lkG7TdfI_QRLnadAr5tjKNQqJtnRXyA2nrUG1LVYXxArW2XVWiM0FVW9eJynTr7eYHFWs0F83iDk0NukZzIz8rhW4IEHJ7EZ1pUXk1ONR-9Pb0OB9P4unr88t4NI1lQoZdLEmquNRSA6e4JIxKrCBNE9AkY6B4UeCylEMsKdVDkIywAGVESBAKMp0k_ehq7xsO_1op3-VLu3JNiMxJlmHCOCQsUHhPSWe9d0rnrTO1cOscQ757bf7ntUGD9holbWP8UZGlhHPKMAlIcrAVdeFMuVDH9P-NfwHtqYW2</recordid><startdate>20231101</startdate><enddate>20231101</enddate><creator>Richards, Stephen J.</creator><general>Cambridge University Press</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7X1</scope><scope>7XB</scope><scope>87Z</scope><scope>8A9</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ANIOZ</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRAZJ</scope><scope>FRNLG</scope><scope>F~G</scope><scope>K60</scope><scope>K6~</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYYUZ</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-6859-6347</orcidid></search><sort><creationdate>20231101</creationdate><title>Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022)</title><author>Richards, Stephen J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c326t-c27e9cfcf0941d254c1e07730f2850e9bb1ddc61c44f60c525d2582ac0ae08f33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Actuarial science</topic><topic>Age</topic><topic>Datasets</topic><topic>Females</topic><topic>Mortality</topic><topic>Original Research Paper</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Richards, Stephen J.</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>ProQuest Central (Corporate)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>Accounting & Tax Database</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Accounting & Tax Database (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Accounting, Tax & Banking Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Accounting, Tax & Banking Collection (Alumni)</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>ABI/INFORM Global</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><jtitle>Annals of actuarial science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Richards, Stephen J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022)</atitle><jtitle>Annals of actuarial science</jtitle><addtitle>Ann. actuar. sci</addtitle><date>2023-11-01</date><risdate>2023</risdate><volume>17</volume><issue>3</issue><spage>643</spage><epage>646</epage><pages>643-646</pages><issn>1748-4995</issn><eissn>1748-5002</eissn><abstract>Tang et al. (2022) propose a new class of models for stochastic mortality modelling using Hermite splines. There are four useful features of this class that are worth emphasising. First, for single-sex datasets, this new class of projection models can be fitted as a generalised linear model. Second, these models can automatically extrapolate mortality rates to ages above the maximum age of the data set. Third, simpler sub-variants of the models exist for forecasting when one of the variables lacks a clear drift. Finally, a minor reparameterisation increases the quality of long-range forecasts of period mortality.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1017/S174849952300012X</doi><tpages>4</tpages><orcidid>https://orcid.org/0000-0001-6859-6347</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1748-4995 |
ispartof | Annals of actuarial science, 2023-11, Vol.17 (3), p.643-646 |
issn | 1748-4995 1748-5002 |
language | eng |
recordid | cdi_proquest_journals_2881259035 |
source | Cambridge University Press Journals Complete |
subjects | Actuarial science Age Datasets Females Mortality Original Research Paper |
title | Some comments on “A Hermite spline approach for modelling population mortality” by Tang, Li & Tickle (2022) |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T16%3A12%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Some%20comments%20on%20%E2%80%9CA%20Hermite%20spline%20approach%20for%20modelling%20population%20mortality%E2%80%9D%20by%20Tang,%20Li%20&%20Tickle%20(2022)&rft.jtitle=Annals%20of%20actuarial%20science&rft.au=Richards,%20Stephen%20J.&rft.date=2023-11-01&rft.volume=17&rft.issue=3&rft.spage=643&rft.epage=646&rft.pages=643-646&rft.issn=1748-4995&rft.eissn=1748-5002&rft_id=info:doi/10.1017/S174849952300012X&rft_dat=%3Cproquest_cross%3E2881259035%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2881259035&rft_id=info:pmid/&rft_cupid=10_1017_S174849952300012X&rfr_iscdi=true |