{"id":5693,"date":"2025-08-06T13:13:27","date_gmt":"2025-08-06T13:13:27","guid":{"rendered":"https:\/\/detralytics.com\/?p=5693"},"modified":"2025-09-10T12:00:05","modified_gmt":"2025-09-10T12:00:05","slug":"statistical-modelling-of-mortality-tableswith-r","status":"publish","type":"post","link":"https:\/\/detralytics.com\/fr\/learning\/actuarial-science\/statistical-modelling-of-mortality-tableswith-r\/","title":{"rendered":"Mod\u00e9lisation statistique des tables de mortalit\u00e9 avec R"},"content":{"rendered":"<div data-elementor-type=\"wp-post\" data-elementor-id=\"5693\" class=\"elementor elementor-5693\" data-elementor-post-type=\"post\">\n\t\t\t\t<div class=\"elementor-element elementor-element-b5596f5 e-con-full e-flex e-con e-parent\" data-id=\"b5596f5\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;classic&quot;,&quot;shape_divider_bottom&quot;:&quot;tilt&quot;}\">\n\t\t\t\t<div class=\"elementor-shape elementor-shape-bottom\" aria-hidden=\"true\" data-negative=\"false\">\n\t\t\t<svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" viewbox=\"0 0 1000 100\" preserveaspectratio=\"none\">\n\t<path class=\"elementor-shape-fill\" d=\"M0,6V0h1000v100L0,6z\"\/>\n<\/svg>\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ffd9fa1 elementor-widget elementor-widget-heading\" data-id=\"ffd9fa1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h1 class=\"elementor-heading-title elementor-size-default\">Mod\u00e9lisation statistique des tables de mortalit\u00e9 avec R<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ffd2db6 elementor-widget elementor-widget-heading\" data-id=\"ffd2db6\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\">D. Hainaut, PhD<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-4fae3a2 e-con-full e-flex e-con e-parent\" data-id=\"4fae3a2\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t<div class=\"elementor-element elementor-element-ab7afb1 e-con-full e-flex e-con e-child\" data-id=\"ab7afb1\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-254f0bc elementor-widget elementor-widget-heading\" data-id=\"254f0bc\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Description<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d2e84fd elementor-widget elementor-widget-text-editor\" data-id=\"d2e84fd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"page\" title=\"Page 3\"><div class=\"layoutArea\"><div class=\"column\"><p class=\"p1\"><span class=\"s1\">Cette formation porte sur l\u2019estimation statistique des tables de mortalit\u00e9 statiques et dynamiques en R. <\/span><\/p><p class=\"p1\"><span class=\"s1\">Apr\u00e8s une introduction g\u00e9n\u00e9rale, nous pr\u00e9sentons les approches non-param\u00e9triques (lissage) et param\u00e9triques (mod\u00e8le statique Poisson, Binomial et Gaussien). Pour illustrations, nous utilisons les packages R MortalityLaws et Demography. <\/span><\/p><p class=\"p1\"><span class=\"s1\">La seconde partie porte sur la construction d\u2019une table de mortalit\u00e9 d\u2019exp\u00e9rience en pr\u00e9sence de censure. Ces tables permettent la comparaison de la mortalit\u00e9 d\u2019exp\u00e9rience de l\u2019assureur \u00e0 la mortalit\u00e9 g\u00e9n\u00e9rale. <\/span><\/p><p class=\"p1\"><span class=\"s1\">La derni\u00e8re partie de ce cours est consacr\u00e9e aux mod\u00e8les dynamiques. Nous d\u00e9butons avec le mod\u00e8le Lee-Carter et comparons l\u2019approche SVD au mod\u00e8le de Poisson. Nous pr\u00e9sentons ensuite les mod\u00e8les CBD et \u00e2ge-p\u00e9riode-cohorte, ainsi que leur impl\u00e9mentation en R \u00e0 l\u2019aide du package STMoMo. <\/span><\/p><p class=\"p1\"><span class=\"s1\">La session est conclue par une introduction aux mod\u00e8les dynamiques \u00e0 populations multiples. Nous \u00e9tudions d\u2019abord le mod\u00e8le Lee-Carter stratifi\u00e9 et l\u2019impl\u00e9mentons en R. Nous pr\u00e9sentons ensuite le mod\u00e8le de Li &amp; Lee et le package R MortalityForecast. Le cours est illustr\u00e9 avec des exemples en Python, fournis aux participants. <\/span><\/p><p class=\"p1\"><span class=\"s1\">Le code R de toutes les illustrations est distribu\u00e9 aux participants.<\/span><\/p><\/div><\/div><\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-79a6580 elementor-widget elementor-widget-heading\" data-id=\"79a6580\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Programme<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d821de4 elementor-widget elementor-widget-text-editor\" data-id=\"d821de4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ol class=\"spaced-list\"><li>Introduction<br \/><br \/><\/li><li><p>Probabilit\u00e9s de survie\/d\u00e9c\u00e8s<\/p><\/li><li>Lecture de donn\u00e9es de HMD en R<ul><li>Avec le package \u201cDemography\u201d<\/li><li>Avec le package \u201cMortalityLaws\u201d<br \/><br \/><\/li><\/ul><\/li><li><p>Probabilit\u00e9s statiques de mortalit\u00e9<\/p><\/li><li>Lissage statique non param\u00e9trique<ul><li>Whittaker Henderson<br \/><br \/><\/li><\/ul><\/li><li>Lissage statique param\u00e9trique<ul><li>Approches : Binomial, Poisson, Gaussien<\/li><li>Gompertz-Makeham en R avec  \u201cMortalityLaws\u201d<\/li><li>Mod\u00e8le Logit et erreurs communes<br \/><br \/><\/li><\/ul><\/li><li>Tables de mortalit\u00e9 d\u2019exp\u00e9rience avec censure<ul><li>Censure : principes g\u00e9n\u00e9raux<\/li><li>Mod\u00e8le de Gompertz-Makeham avec censure \u00e0 droite<br \/><br \/><\/li><\/ul><\/li><li>Tables de mortalit\u00e9 prospectives<ul><li>Exposition au risque ?<\/li><li>Mod\u00e8les Lee-Carter, Poisson et CBD<\/li><li>Lee-Carter, package Demography<\/li><li>Mod\u00e8le Age-P\u00e9riode-Cohorte<\/li><li>Tables prospectives avec le Package \u201cStMoMo\u201d<br \/><br \/><\/li><\/ul><\/li><li>Tables multi-populations prospectives<ul><li>Mod\u00e8le Poisson Lee-Carter stratifi\u00e9 et  impl\u00e9mentation en R<\/li><li>Mod\u00e8le de Li and Lee<\/li><li>Introduction au Package \u201cMortalityForecast\u201d<\/li><\/ul><\/li><\/ol>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-7daa359 e-con-full e-flex e-con e-child\" data-id=\"7daa359\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-355647c elementor-widget elementor-widget-heading\" data-id=\"355647c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Orateur<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-2a56262 elementor-widget elementor-widget-image\" data-id=\"2a56262\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img fetchpriority=\"high\" decoding=\"async\" width=\"1042\" height=\"1042\" src=\"https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond.jpg\" class=\"attachment-full size-full wp-image-2876\" alt=\"Donatien Hainaut\" srcset=\"https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond.jpg 1042w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-768x768.jpg 768w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-146x146.jpg 146w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-50x50.jpg 50w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-75x75.jpg 75w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-85x85.jpg 85w, https:\/\/detralytics.com\/wp-content\/uploads\/2023\/07\/Donatien_Rond-80x80.jpg 80w\" sizes=\"(max-width: 1042px) 100vw, 1042px\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-ab825d4 elementor-widget elementor-widget-heading\" data-id=\"ab825d4\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Donatien Hainaut<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-d353b87 elementor-widget elementor-widget-text-editor\" data-id=\"d353b87\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><em>Conseiller Scientifique, Detralytics<\/em><br \/><em>Professeur, UCLouvain<\/em><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-0f29719 e-con-full e-flex e-con e-child\" data-id=\"0f29719\" data-element_type=\"container\" data-e-type=\"container\" data-settings=\"{&quot;background_background&quot;:&quot;gradient&quot;}\">\n\t\t\t\t<div class=\"elementor-element elementor-element-5de7e2a elementor-widget elementor-widget-text-editor\" data-id=\"5de7e2a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p><b>Date : <\/b>\u00c0 la demande<\/p><p><b><\/b><b>Dur\u00e9e : <\/b>9h<\/p><p><b style=\"letter-spacing: 0.3px; background-color: transparent;\">Accr\u00e9ditation :<\/b><span style=\"letter-spacing: 0.3px; background-color: transparent;\"> 9CPD | 54PPC<\/span><\/p><p><b>Niveau :<\/b> Tout<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-678e6db e-con-full e-flex e-con e-child\" data-id=\"678e6db\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-898935e elementor-align-center elementor-widget elementor-widget-button\" data-id=\"898935e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"mailto:learning@detralytics.eu\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Introduire une demande<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-07e40ea e-con-full e-flex e-con e-child\" data-id=\"07e40ea\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-89b6347 e-con-full e-flex e-con e-parent\" data-id=\"89b6347\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-383049d elementor-widget elementor-widget-heading\" data-id=\"383049d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Comp\u00e9tences acquises<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-bc0d89b elementor-widget elementor-widget-text-editor\" data-id=\"bc0d89b\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p class=\"p2 translation-block\">Au terme de ce cours, les participants seront capables de traiter les donn\u00e9es de mortalit\u00e9 disponibles sur le web en R, d\u2019estimer en R tout mod\u00e8le statique param\u00e9trique avec une m\u00e9thode statistique rigoureuse en \u00e9vitant les erreurs habituelles, de construire une table de mortalit\u00e9 d\u2019exp\u00e9rience et de g\u00e9rer la censure. Ils sauront \u00e9galement  g\u00e9n\u00e9rer des tables de mortalit\u00e9 prospective avec les mod\u00e8les Age-P\u00e9riode-Cohorte et ses variantes, utiliser les packages R, MortalityLaws, Demography, StMoMo, MortalityForecast, estimer un mod\u00e8le \u00e0 populations multiples et d\u00e9velopper son propre code impl\u00e9mentant un mod\u00e8le non-standard.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-6d47b7c e-con-full e-flex e-con e-parent\" data-id=\"6d47b7c\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-cc3d72a elementor-widget elementor-widget-heading\" data-id=\"cc3d72a\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">\u00c0 propos des orateurs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-224cb75 elementor-widget elementor-widget-heading\" data-id=\"224cb75\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h2 class=\"elementor-heading-title elementor-size-default\">Donatien Hainaut<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-58dff6d elementor-widget elementor-widget-text-editor\" data-id=\"58dff6d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p class=\"has-text-color has-link-color wp-elements-ae5c48d82f22f2e0c01ebb851eee595b\">Donatien Hainaut est Conseiller Scientifique chez Detralytics et Professeur \u00e0 l\u2019UCLouvain (Belgique), o\u00f9 il dirige le Master en Data Science \u00e0 orientation statistique. Auparavant, il a occup\u00e9 plusieurs postes acad\u00e9miques, notamment en tant que Professeur Associ\u00e9 \u00e0 la Rennes School of Business et \u00e0 l\u2019ENSAE \u00e0 Paris. Il poss\u00e8de \u00e9galement une solide exp\u00e9rience en entreprise, ayant travaill\u00e9 comme Risk Officer, Quantitative Analyst et ALM Officer.<\/p><p class=\"has-text-color has-link-color wp-elements-319687f5e483df5041193c0b748e25dd\">Actuaire qualifi\u00e9 et titulaire d\u2019un doctorat en Asset and Liability Management, ses recherches actuelles portent sur les m\u00e9canismes de contagion dans les processus stochastiques ainsi que sur les applications des r\u00e9seaux de neurones en assurance.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t<div class=\"elementor-element elementor-element-871632e e-con-full e-flex e-con e-parent\" data-id=\"871632e\" data-element_type=\"container\" data-e-type=\"container\">\n\t\t\t\t<div class=\"elementor-element elementor-element-599d398 elementor-align-center elementor-widget elementor-widget-button\" data-id=\"599d398\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"button.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-button-wrapper\">\n\t\t\t\t\t<a class=\"elementor-button elementor-button-link elementor-size-sm\" href=\"https:\/\/detralytics.com\/fr\/trainings\/#opentrainings\">\n\t\t\t\t\t\t<span class=\"elementor-button-content-wrapper\">\n\t\t\t\t\t\t<span class=\"elementor-button-icon\">\n\t\t\t\t<svg aria-hidden=\"true\" class=\"e-font-icon-svg e-fas-arrow-right\" viewbox=\"0 0 448 512\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\"><path d=\"M190.5 66.9l22.2-22.2c9.4-9.4 24.6-9.4 33.9 0L441 239c9.4 9.4 9.4 24.6 0 33.9L246.6 467.3c-9.4 9.4-24.6 9.4-33.9 0l-22.2-22.2c-9.5-9.5-9.3-25 .4-34.3L311.4 296H24c-13.3 0-24-10.7-24-24v-32c0-13.3 10.7-24 24-24h287.4L190.9 101.2c-9.8-9.3-10-24.8-.4-34.3z\"><\/path><\/svg>\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t<span class=\"elementor-button-text\">Nos formations<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"<p>Cette formation porte sur l\u2019estimation statistique des tables de mortalit\u00e9 statiques et dynamiques en R. <\/p>","protected":false},"author":1,"featured_media":5704,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[151],"tags":[148],"class_list":["post-5693","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-actuarial-science","tag-actuarial-science"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Training : Statistical modelling of mortality tables with R<\/title>\n<meta name=\"description\" content=\"Participants will be able to find mortality data available on the 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