{"id":669,"date":"2011-11-14T11:05:39","date_gmt":"2011-11-14T10:05:39","guid":{"rendered":"https:\/\/abcdr.guyader.pro\/?p=669"},"modified":"2018-04-07T23:59:37","modified_gmt":"2018-04-07T22:59:37","slug":"comment-tracer-un-diagramme-quantile-quantile-avec-r-qq-plot","status":"publish","type":"post","link":"https:\/\/thinkr.fr\/abcdr\/comment-tracer-un-diagramme-quantile-quantile-avec-r-qq-plot\/","title":{"rendered":"Comment tracer un diagramme Quantile-Quantile avec R ? : QQ-plot"},"content":{"rendered":"<p>Le diagramme Quantile-Quantile est un outil graphique qui permet de comparer la pertinence de l&rsquo;ajustement de donn\u00e9es \u00e0 un mod\u00e8le th\u00e9orique (loi de probabilit\u00e9). Cela peut se r\u00e9v\u00e9ler tr\u00e8s pratique pour analyser la normalit\u00e9 des r\u00e9sidus d&rsquo;un mod\u00e8le lin\u00e9aire par exemple.<\/p>\n<p>Cet outil permet \u00e9galement de comparer deux distributions : un alignement selon la premi\u00e8re bissectrice indique la pr\u00e9sence d&rsquo;une identit\u00e9 de loi.<\/p>\n<p>R pr\u00e9sente des fonctions de bases permettant de tracer des QQplot :<\/p>\n<p><strong>qqplot<\/strong> produit un QQplot de deux jeux de donn\u00e9es<br \/><strong>qqnorm<\/strong> produit un QQplot pour une loi normale<br \/><strong>qqline<\/strong> trace la droite de Henry<\/p>\n<p>Voyons un exemple d&rsquo;utilisation<\/p>\n<pre><code><br \/><br \/> <br \/>#nombres al\u00e9atoires tir\u00e9s d'une loi<br \/><br \/>#normale de moyenne 0 et d'\u00e9cart-type 1<br \/>a&lt;-rnorm(100,mean=0,sd=1)<br \/><br \/>#gamma<br \/>b&lt;-rgamma(100,shape=1,rate=0.8)<br \/><br \/>#normale de moyenne 0.5 et d'\u00e9cart-type 0.5<br \/>c&lt;-rnorm(100,mean=0.5,sd=0.5)<br \/><br \/>#on visualise tout \u00e7a sur un graphique<br \/><br \/>x11()<br \/>plot(a,pch=20,ylim=c(-5,5))<br \/>points(b,pch=20,col=\"blue\")<br \/>points(c,pch=20,col=\"grey\")<br \/>legend(\"bottomleft\",legend=c(\"nombres al\u00e9atoires loi normale1\",<br \/>\u00a0\u00a0 \u00a0\"nombres al\u00e9atoires loi gamma\",\"nombres al\u00e9atoires loi normale2\"),<br \/>\u00a0\u00a0 \u00a0col=c(\"black\",\"blue\",\"grey\"),pch=20)<br \/><br \/><br \/>x11()<br \/>par(mfrow=c(2,2))<br \/><br \/>qqnorm(a,main=\"QQ plot a\")<br \/>qqline(a)<br \/><br \/>qqnorm(b,main=\"QQplot b\")<br \/>qqline(b)<br \/><br \/>qqplot(b,a,main=\"QQplot b et a\")<br \/><br \/>qqplot(a,c,main=\"QQplot a et c\") <br \/><br \/><\/code><\/pre>\n<p>Il existe d&rsquo;autres fonctions permettant de tracer des QQplots. La fonction qqmath du package Lattice permet, elle, de tracer des QQplot pour d&rsquo;autres distributions th\u00e9oriques (qqnorm compare \u00e0 une loi normale).<\/p>\n<p>Bon QQplot!<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Le diagramme Quantile-Quantile est un outil graphique qui permet de comparer la pertinence de l&rsquo;ajustement de donn\u00e9es \u00e0 un mod\u00e8le th\u00e9orique (loi de probabilit\u00e9). Cela peut se r\u00e9v\u00e9ler tr\u00e8s pratique pour analyser la normalit\u00e9 des r\u00e9sidus d&rsquo;un mod\u00e8le lin\u00e9aire par exemple. Cet outil permet \u00e9galement de comparer deux distributions : un alignement selon la premi\u00e8re bissectrice indique la pr\u00e9sence d&rsquo;une identit\u00e9 de loi. R pr\u00e9sente des fonctions de bases permettant de tracer des QQplot : qqplot produit un QQplot de deux jeux de donn\u00e9esqqnorm produit un QQplot pour une loi normaleqqline trace la droite de Henry Voyons un exemple d&rsquo;utilisation #nombres al\u00e9atoires tir\u00e9s d&rsquo;une loi#normale<a class=\"more-link\" href=\"https:\/\/thinkr.fr\/abcdr\/comment-tracer-un-diagramme-quantile-quantile-avec-r-qq-plot\/\">Read More &rarr;<\/a><\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","rop_custom_images_group":[],"rop_custom_messages_group":[],"rop_publish_now":"initial","rop_publish_now_accounts":{"twitter_399453572_399453572":""},"rop_publish_now_history":[],"rop_publish_now_status":"pending","jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[4],"tags":[],"class_list":{"0":"entry","1":"post","2":"publish","3":"author-melen","4":"post-669","6":"format-standard","7":"category-base-indispensable"},"acf":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p9O7Sx-aN","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/669","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/comments?post=669"}],"version-history":[{"count":2,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/669\/revisions"}],"predecessor-version":[{"id":4129,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/posts\/669\/revisions\/4129"}],"wp:attachment":[{"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/media?parent=669"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/categories?post=669"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thinkr.fr\/abcdr\/wp-json\/wp\/v2\/tags?post=669"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}