{"id":1313,"date":"2023-07-26T22:13:41","date_gmt":"2023-07-26T22:13:41","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%a0%87%e5%87%86%e5%8c%96%e7%9a%84python%e6%ae%8b%e5%9f%ba\/"},"modified":"2023-07-26T22:13:41","modified_gmt":"2023-07-26T22:13:41","slug":"%e6%a0%87%e5%87%86%e5%8c%96%e7%9a%84python%e6%ae%8b%e5%9f%ba","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%a0%87%e5%87%86%e5%8c%96%e7%9a%84python%e6%ae%8b%e5%9f%ba\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u8ba1\u7b97\u6807\u51c6\u5316\u6b8b\u5dee"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u6b8b\u5dee<\/strong>\u662f<a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f521\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u56de\u5f52\u6a21\u578b<\/a>\u4e2d\u89c2\u6d4b\u503c\u4e0e\u9884\u6d4b\u503c\u4e4b\u95f4\u7684\u5dee\u5f02\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8ba1\u7b97\u65b9\u6cd5\u5982\u4e0b\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6b8b\u5dee = \u89c2\u6d4b\u503c \u2013 \u9884\u6d4b\u503c<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u6211\u4eec\u7ed8\u5236\u89c2\u6d4b\u503c\u5e76\u53e0\u52a0\u62df\u5408\u56de\u5f52\u7ebf\uff0c\u5219\u6bcf\u4e2a<a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u89c2\u5bdf\/\" target=\"_blank\" rel=\"noopener\">\u89c2\u6d4b\u503c<\/a>\u7684\u6b8b\u5dee\u5c06\u662f\u89c2\u6d4b\u503c\u4e0e\u56de\u5f52\u7ebf\u4e4b\u95f4\u7684\u5782\u76f4\u8ddd\u79bb\uff1a<\/span> <\/p>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-12422 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/residus1-1.png\" alt=\"\u7edf\u8ba1\u4e2d\u7684\u6b8b\u5dee\u793a\u4f8b\" width=\"487\" height=\"382\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u7ecf\u5e38\u7528\u6765\u8bc6\u522b\u56de\u5f52\u6a21\u578b\u4e2d\u7684\u5f02\u5e38\u503c\u7684\u4e00\u79cd\u6b8b\u5dee\u79f0\u4e3a<strong>\u6807\u51c6\u5316\u6b8b\u5dee<\/strong>\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8ba1\u7b97\u65b9\u6cd5\u5982\u4e0b\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>r <sub>i<\/sub> = e <sub>i<\/sub> \/ s(e <sub>i<\/sub> )<\/strong> = <strong>e <sub>i<\/sub> \/ RSE\u221a <span style=\"border-top: 1px solid black;\">1-h <sub>ii<\/sub><\/span><\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>e <sub>i<\/sub> :<\/strong>\u7b2c i<sup>\u4e2a<\/sup>\u6b8b\u57fa<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>RSE\uff1a<\/strong>\u6a21\u578b\u7684\u6b8b\u5dee\u6807\u51c6\u8bef\u5dee<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>h <sub>ii<\/sub><\/strong> \uff1a<sup>\u7b2c i \u4e2a<\/sup>\u89c2\u6d4b\u503c\u7684\u4e0a\u5347<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5728\u5b9e\u8df5\u4e2d\uff0c\u6211\u4eec\u7ecf\u5e38\u5c06\u7edd\u5bf9\u503c\u5927\u4e8e 3 \u7684\u4efb\u4f55\u6807\u51c6\u5316\u6b8b\u5dee\u89c6\u4e3a\u5f02\u5e38\u503c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u63d0\u4f9b\u4e86\u5982\u4f55\u5728 Python \u4e2d\u8ba1\u7b97\u6807\u51c6\u5316\u6b8b\u5dee\u7684\u5206\u6b65\u793a\u4f8b\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u7b2c 1 \u6b65\uff1a\u8f93\u5165\u6570\u636e<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u5c06\u521b\u5efa\u4e00\u4e2a\u5728 Python \u4e2d\u4f7f\u7528\u7684\u5c0f\u6570\u636e\u96c6\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008000;\">import<\/span> pandas <span style=\"color: #008000;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create dataset\n<\/span>df = pd. <span style=\"color: #3366ff;\">DataFrame<\/span> ({' <span style=\"color: #008000;\">x<\/span> ': [8, 12, 12, 13, 14, 16, 17, 22, 24, 26, 29, 30],\n                   ' <span style=\"color: #008000;\">y<\/span> ': [41, 42, 39, 37, 35, 39, 45, 46, 39, 49, 55, 57]})\n<\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 2\uff1a\u62df\u5408\u56de\u5f52\u6a21\u578b<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u62df\u5408\u4e00\u4e2a<a href=\"https:\/\/statorials.org\/cn\/python-\u4e2d\u7684\u7b80\u5355\u7ebf\u6027\u56de\u5f52\/\" target=\"_blank\" rel=\"noopener\">\u7b80\u5355\u7684\u7ebf\u6027\u56de\u5f52\u6a21\u578b<\/a>\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <span style=\"color: #000000;\"><strong><span style=\"color: #008000;\">import<\/span> statsmodels. <span style=\"color: #3366ff;\">api<\/span> <span style=\"color: #008000;\">as<\/span> sm\n\n<span style=\"color: #008080;\">#define response variable\n<\/span>y = df[' <span style=\"color: #008000;\">y<\/span> ']\n\n<span style=\"color: #008080;\">#define explanatory variable\n<\/span>x = df[' <span style=\"color: #008000;\">x<\/span> ']\n\n<span style=\"color: #008080;\">#add constant to predictor variables\n<\/span>x = sm. <span style=\"color: #3366ff;\">add_constant<\/span> (x)\n\n<span style=\"color: #008080;\">#fit linear regression model\n<\/span>model = sm. <span style=\"color: #3366ff;\">OLS<\/span> (y,x). <span style=\"color: #3366ff;\">fit<\/span> ()<\/strong><\/span><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 3\uff1a\u8ba1\u7b97\u6807\u51c6\u5316\u6b8b\u5dee<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u8ba1\u7b97\u6a21\u578b\u7684\u6807\u51c6\u5316\u6b8b\u5dee\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create instance of influence\n<\/span>influence = model. <span style=\"color: #3366ff;\">get_influence<\/span> ()\n\n<span style=\"color: #008080;\">#obtain standardized residuals\n<\/span>standardized_residuals = influence. <span style=\"color: #3366ff;\">reside_studentized_internal<\/span>\n\n<span style=\"color: #008080;\">#display standardized residuals\n<\/span><span style=\"color: #993300;\">print<\/span> (standardized_residuals)\n\n[ 1.40517322 0.81017562 0.07491009 -0.59323342 -1.2482053 -0.64248883\n  0.59610905 -0.05876884 -2.11711982 -0.066556 0.91057211 1.26973888]<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ece\u7ed3\u679c\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u6ca1\u6709\u4e00\u4e2a\u6807\u51c6\u5316\u6b8b\u5dee\u7684\u7edd\u5bf9\u503c\u8d85\u8fc7 3\u3002\u56e0\u6b64\uff0c\u6ca1\u6709\u4e00\u4e2a\u89c2\u6d4b\u503c\u770b\u8d77\u6765\u662f\u5f02\u5e38\u503c\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 4\uff1a\u53ef\u89c6\u5316\u6807\u51c6\u5316\u6b8b\u5dee<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u521b\u5efa\u4e00\u4e2a\u6563\u70b9\u56fe\u6765\u53ef\u89c6\u5316\u9884\u6d4b\u53d8\u91cf\u503c\u4e0e\u6807\u51c6\u5316\u6b8b\u5dee\u7684\u5173\u7cfb\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\"><span style=\"color: #000000;\"><span style=\"color: #008000;\">import<\/span> matplotlib. <span style=\"color: #3366ff;\">pyplot<\/span> <span style=\"color: #008000;\">as<\/span> plt\n\nplt. <span style=\"color: #3366ff;\">scatter<\/span> (df.x, standardized_residuals)\nplt. <span style=\"color: #3366ff;\">xlabel<\/span> (' <span style=\"color: #008000;\">x<\/span> ')\nplt. <span style=\"color: #3366ff;\">ylabel<\/span> (' <span style=\"color: #008000;\">Standardized Residuals<\/span> ')\nplt. <span style=\"color: #3366ff;\">axhline<\/span> (y=0, color=' <span style=\"color: #008000;\">black<\/span> ', linestyle=' <span style=\"color: #008000;\">--<\/span> ', linewidth=1)\nplt. <span style=\"color: #3366ff;\">show<\/span> ()<\/span><\/span><\/strong><\/pre>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/cn\/\u6b8b\u7559\u7269\/\" target=\"_blank\" rel=\"noopener\">\u4ec0\u4e48\u662f\u6b8b\u7559\u7269\uff1f<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u6807\u51c6\u5316\u6b8b\u7559\u91cf\/\">\u4ec0\u4e48\u662f\u6807\u51c6\u5316\u6b8b\u5dee\uff1f<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/r-\u4e2d\u6807\u51c6\u5316\u7684\u6b8b\u7559\u7269\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u8ba1\u7b97 R \u4e2d\u7684\u6807\u51c6\u5316\u6b8b\u5dee<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/excel\u6807\u51c6\u5316\u6b8b\u5dee\/\" target=\"_blank\" rel=\"noopener\">\u5982\u4f55\u5728Excel\u4e2d\u8ba1\u7b97\u6807\u51c6\u5316\u6b8b\u5dee<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u6b8b\u5dee\u662f\u56de\u5f52\u6a21\u578b\u4e2d\u89c2\u6d4b\u503c\u4e0e\u9884\u6d4b\u503c\u4e4b\u95f4\u7684\u5dee\u5f02\u3002 \u8ba1\u7b97\u65b9\u6cd5\u5982\u4e0b\uff1a \u6b8b\u5dee = \u89c2\u6d4b\u503c \u2013 \u9884\u6d4b\u503c \u5982\u679c\u6211\u4eec\u7ed8\u5236\u89c2\u6d4b\u503c\u5e76 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11],"tags":[],"class_list":["post-1313","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>\u5982\u4f55\u5728 Python \u4e2d\u8ba1\u7b97\u6807\u51c6\u5316\u6b8b\u5dee<\/title>\n<meta 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