{"id":1534,"date":"2023-07-25T23:59:19","date_gmt":"2023-07-25T23:59:19","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e8%b4%9f%e4%ba%8c%e9%a1%b9%e5%bc%8f%e4%b8%8e%e9%b1%bc\/"},"modified":"2023-07-25T23:59:19","modified_gmt":"2023-07-25T23:59:19","slug":"%e8%b4%9f%e4%ba%8c%e9%a1%b9%e5%bc%8f%e4%b8%8e%e9%b1%bc","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e8%b4%9f%e4%ba%8c%e9%a1%b9%e5%bc%8f%e4%b8%8e%e9%b1%bc\/","title":{"rendered":"\u8d1f\u4e8c\u9879\u5f0f\u4e0e\u6cca\u677e\uff1a\u5982\u4f55\u9009\u62e9\u56de\u5f52\u6a21\u578b"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><strong>\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52<\/strong>\u548c<strong>\u6cca\u677e\u56de\u5f52<\/strong>\u662f\u5f53<a href=\"https:\/\/statorials.org\/cn\/\u53d8\u91cf\u89e3\u91ca\u6027\u53cd\u5e94\/\" target=\"_blank\" rel=\"noopener\">\u54cd\u5e94\u53d8\u91cf<\/a>\u7531\u79bb\u6563\u8ba1\u6570\u7ed3\u679c\u8868\u793a\u65f6\u5e94\u4f7f\u7528\u7684\u4e24\u79cd\u56de\u5f52\u6a21\u578b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u4ee3\u8868\u79bb\u6563\u8ba1\u6570\u7ed3\u679c\u7684\u54cd\u5e94\u53d8\u91cf\u7684\u4e00\u4e9b\u793a\u4f8b\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u4ece\u67d0\u4e2a\u8bfe\u7a0b\u6bd5\u4e1a\u7684\u5b66\u751f\u4eba\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\">\u67d0\u4e2a\u8def\u53e3\u53d1\u751f\u4ea4\u901a\u4e8b\u6545\u7684\u6570\u91cf<\/span><\/li>\n<li><span style=\"color: #000000;\">\u5b8c\u6210\u9a6c\u62c9\u677e\u6bd4\u8d5b\u7684\u4eba\u6570<\/span><\/li>\n<li><span style=\"color: #000000;\">\u96f6\u552e\u5e97\u6307\u5b9a\u6708\u4efd\u7684\u9000\u8d27\u6570\u91cf<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5982\u679c\u65b9\u5dee\u8fd1\u4f3c\u7b49\u4e8e\u5e73\u5747\u503c\uff0c\u5219\u6cca\u677e\u56de\u5f52\u6a21\u578b\u901a\u5e38\u53ef\u4ee5\u5f88\u597d\u5730\u62df\u5408\u6570\u636e\u96c6\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f46\u662f\uff0c\u5982\u679c\u65b9\u5dee\u663e\u7740\u5927\u4e8e\u5e73\u5747\u503c\uff0c\u5219\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u901a\u5e38\u80fd\u591f\u66f4\u597d\u5730\u62df\u5408\u6570\u636e\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4e24\u79cd\u6280\u672f\u6765\u786e\u5b9a\u6cca\u677e\u56de\u5f52\u8fd8\u662f\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u66f4\u9002\u5408\u7ed9\u5b9a\u7684\u6570\u636e\u96c6\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1.\u6b8b\u5dee\u56fe<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u6839\u636e\u56de\u5f52\u6a21\u578b\u7684\u9884\u6d4b\u503c\u521b\u5efa\u6807\u51c6\u5316\u6b8b\u5dee\u56fe\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u5927\u591a\u6570\u6807\u51c6\u5316\u6b8b\u5dee\u5728 -2 \u548c 2 \u4e4b\u95f4\uff0c\u5219\u6cca\u677e\u56de\u5f52\u6a21\u578b\u53ef\u80fd\u662f\u5408\u9002\u7684\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f46\u662f\uff0c\u5982\u679c\u8bb8\u591a\u6b8b\u5dee\u8d85\u51fa\u6b64\u8303\u56f4\uff0c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u53ef\u80fd\u4f1a\u63d0\u4f9b\u66f4\u597d\u7684\u62df\u5408\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2.\u4f3c\u7136\u6bd4\u68c0\u9a8c<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u5c06\u6cca\u677e\u56de\u5f52\u6a21\u578b\u548c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u62df\u5408\u5230\u540c\u4e00\u6570\u636e\u96c6\uff0c\u7136\u540e\u8fdb\u884c\u4f3c\u7136\u6bd4\u68c0\u9a8c\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5982\u679c\u68c0\u9a8c\u7684 p \u503c\u4f4e\u4e8e\u4e00\u5b9a\u7684\u663e\u7740\u6027\u6c34\u5e73\uff08\u4f8b\u5982 0.05\uff09\uff0c\u90a3\u4e48\u6211\u4eec\u53ef\u4ee5\u5f97\u51fa\u7ed3\u8bba\uff0c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u63d0\u4f9b\u4e86\u660e\u663e\u66f4\u597d\u7684\u62df\u5408\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u6f14\u793a\u5982\u4f55\u5728 R \u4e2d\u4f7f\u7528\u8fd9\u4e24\u79cd\u6280\u672f\u6765\u786e\u5b9a\u5bf9\u4e8e\u7ed9\u5b9a\u6570\u636e\u96c6\u662f\u4f7f\u7528\u6cca\u677e\u56de\u5f52\u6a21\u578b\u8fd8\u662f\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u66f4\u597d\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1a\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u4e0e\u6cca\u677e\u56de\u5f52<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u60f3\u77e5\u9053\u7ed9\u5b9a\u53bf\u7684\u4e00\u540d\u9ad8\u4e2d\u68d2\u7403\u8fd0\u52a8\u5458\u6839\u636e\u4ed6\u7684\u5b66\u533a\uff08\u201cA\u201d\u3001\u201cB\u201d\u6216\u201cC\u201d\uff09\u548c\u4ed6\u7684\u5b66\u6821\u6210\u7ee9\u83b7\u5f97\u4e86\u591a\u5c11\u5956\u5b66\u91d1\u3002\u5927\u5b66\u5165\u5b66\u8003\u8bd5\uff08\u4ece0\u5230100\u6d4b\u91cf\uff09\u3002 \uff09\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4f7f\u7528\u4ee5\u4e0b\u6b65\u9aa4\u786e\u5b9a\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u8fd8\u662f\u6cca\u677e\u56de\u5f52\u6a21\u578b\u662f\u5426\u80fd\u66f4\u597d\u5730\u62df\u5408\u6570\u636e\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u7b2c 1 \u6b65\uff1a\u521b\u5efa\u6570\u636e<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u521b\u5efa\u6211\u4eec\u5c06\u4f7f\u7528\u7684\u6570\u636e\u96c6\uff0c\u5176\u4e2d\u5305\u62ec 1,000 \u540d\u68d2\u7403\u8fd0\u52a8\u5458\u7684\u6570\u636e\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set. <span style=\"color: #3366ff;\">seeds<\/span> (1)\n\n<span style=\"color: #008080;\">#create dataset\n<\/span>data &lt;- data. <span style=\"color: #3366ff;\">frame<\/span> (offers = c(rep(0, 700), rep(1, 100), rep(2, 100),\n                              rep(3, 70), rep(4, 30)),\n                   division = sample(c(' <span style=\"color: #008000;\">A<\/span> ', ' <span style=\"color: #008000;\">B<\/span> ', ' <span style=\"color: #008000;\">C<\/span> '), 100, replace = <span style=\"color: #008000;\">TRUE<\/span> ),\n                   exam = c(runif(700, 60, 90), runif(100, 65, 95),\n                            runif(200, 75, 95)))\n\n<span style=\"color: #008080;\">#view first six rows of dataset\n<\/span>head(data)\n\n  offers division exam\n1 0 A 66.22635\n2 0 C 66.85974\n3 0 A 77.87136\n4 0 B 77.24617\n5 0 A 62.31193\n6 0 C 61.06622<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 2\uff1a\u62df\u5408\u6cca\u677e\u56de\u5f52\u6a21\u578b\u548c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u5982\u4f55\u5c06\u6cca\u677e\u56de\u5f52\u6a21\u578b\u548c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u62df\u5408\u5230\u6570\u636e\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit Poisson regression model\n<\/span>p_model &lt;- glm(offers ~ division + exam, family = ' <span style=\"color: #008000;\">fish<\/span> ', data = data)\n\n<span style=\"color: #008080;\">#fit negative binomial regression model\n<\/span><span style=\"color: #993300;\">library<\/span> (MASS)\n\nnb_model &lt;- glm. <span style=\"color: #3366ff;\">nb<\/span> (offers ~ division + exam, data = data)\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><strong>\u7b2c 3 \u6b65\uff1a\u521b\u5efa\u6b8b\u5dee\u56fe<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u4e3a\u4e24\u4e2a\u6a21\u578b\u751f\u6210\u6b8b\u5dee\u56fe\u3002<\/span> <\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#Residual plot for Poisson regression\n<\/span>p_res &lt;- <span style=\"color: #3366ff;\">resid<\/span> (p_model)\nplot(fitted(p_model), p_res, col=' <span style=\"color: #008000;\">steelblue<\/span> ', pch=16,\n     xlab=' <span style=\"color: #008000;\">Predicted Offers<\/span> ', ylab=' <span style=\"color: #008000;\">Standardized Residuals<\/span> ', main=' <span style=\"color: #008000;\">Poisson<\/span> ')\nabline(0,0)\n\n<span style=\"color: #008080;\">#Residual plot for negative binomial regression<\/span>\nnb_res &lt;- <span style=\"color: #3366ff;\">resid<\/span> (nb_model)\nplot(fitted(nb_model), nb_res, col=' <span style=\"color: #008000;\">steelblue<\/span> ', pch=16,\n     xlab=' <span style=\"color: #008000;\">Predicted Offers<\/span> ', ylab=' <span style=\"color: #008000;\">Standardized Residuals<\/span> ', main=' <span style=\"color: #008000;\">Negative Binomial<\/span> ')\nabline(0,0)<\/strong> <\/pre>\n<p><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-15231 \" src=\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/negatifbinom1.png\" alt=\"\u8d1f\u4e8c\u9879\u56de\u5f52\u4e0e\u6cca\u677e\u56de\u5f52\" width=\"679\" height=\"327\" srcset=\"\" sizes=\"auto, \"><\/p>\n<p><span style=\"color: #000000;\">\u4ece\u56fe\u4e2d\u6211\u4eec\u53ef\u4ee5\u770b\u5230\uff0c\u4e0e\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u76f8\u6bd4\uff0c\u6cca\u677e\u56de\u5f52\u6a21\u578b\u7684\u6b8b\u5dee\u5206\u5e03\u5f97\u66f4\u5e7f\uff08\u8bf7\u6ce8\u610f\uff0c\u6709\u4e9b\u6b8b\u5dee\u8d85\u51fa\u4e86 3\uff09\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8fd9\u8868\u660e\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u53ef\u80fd\u66f4\u5408\u9002\uff0c\u56e0\u4e3a\u8be5\u6a21\u578b\u7684\u6b8b\u5dee\u8f83\u5c0f\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u6b65\u9aa4 4\uff1a\u6267\u884c\u4f3c\u7136\u6bd4\u68c0\u9a8c<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6700\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u4f3c\u7136\u6bd4\u68c0\u9a8c\u6765\u786e\u5b9a\u4e24\u4e2a\u56de\u5f52\u6a21\u578b\u7684\u62df\u5408\u662f\u5426\u5b58\u5728\u7edf\u8ba1\u4e0a\u663e\u7740\u7684\u5dee\u5f02\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong>pchisq(2 * ( <span style=\"color: #3366ff;\">logLik<\/span> (nb_model) - <span style=\"color: #3366ff;\">logLik<\/span> (p_model)), df = 1, lower. <span style=\"color: #3366ff;\">tail<\/span> = <span style=\"color: #008000;\">FALSE<\/span> )\n\n'log Lik.' 3.508072e-29 (df=5)\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6d4b\u8bd5\u7684 p \u503c\u4e3a<strong>3.508072e-29<\/strong> \uff0c\u660e\u663e\u5c0f\u4e8e 0.05\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u56e0\u6b64\uff0c\u6211\u4eec\u53ef\u4ee5\u5f97\u51fa\u7ed3\u8bba\uff0c\u4e0e\u6cca\u677e\u56de\u5f52\u6a21\u578b\u76f8\u6bd4\uff0c\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u6a21\u578b\u5bf9\u6570\u636e\u7684\u62df\u5408\u6548\u679c\u660e\u663e\u66f4\u597d\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n<p><a href=\"https:\/\/statorials.org\/cn\/\u8d1f-1-\u4e8c\u9879\u5206\u5e03\/\" target=\"_blank\" rel=\"noopener\">\u8d1f\u4e8c\u9879\u5206\u5e03\u7b80\u4ecb<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u9c7c\u7c7b\u5206\u5e03\/\" target=\"_blank\" rel=\"noopener\">\u6cca\u677e\u5206\u5e03\u7b80\u4ecb<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u8d1f\u4e8c\u9879\u5f0f\u56de\u5f52\u548c\u6cca\u677e\u56de\u5f52\u662f\u5f53\u54cd\u5e94\u53d8\u91cf\u7531\u79bb\u6563\u8ba1\u6570\u7ed3\u679c\u8868\u793a\u65f6\u5e94\u4f7f\u7528\u7684\u4e24\u79cd\u56de\u5f52\u6a21\u578b\u3002 \u4ee5\u4e0b\u662f\u4ee3\u8868\u79bb\u6563\u8ba1\u6570\u7ed3\u679c\u7684\u54cd\u5e94\u53d8\u91cf [&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-1534","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - 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