{"id":872,"date":"2023-07-28T11:41:06","date_gmt":"2023-07-28T11:41:06","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%9d%9c%e5%ae%be%e6%b2%83%e6%a3%ae%e6%b5%8b%e8%af%95python\/"},"modified":"2023-07-28T11:41:06","modified_gmt":"2023-07-28T11:41:06","slug":"%e6%9d%9c%e5%ae%be%e6%b2%83%e6%a3%ae%e6%b5%8b%e8%af%95python","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%9d%9c%e5%ae%be%e6%b2%83%e6%a3%ae%e6%b5%8b%e8%af%95python\/","title":{"rendered":"\u5982\u4f55\u5728 python \u4e2d\u6267\u884c durbin-watson \u6d4b\u8bd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f52\u5047\u8bbe\/\" target=\"_blank\" rel=\"noopener\">\u7ebf\u6027\u56de\u5f52\u7684\u5047\u8bbe<\/a><span style=\"color: #000000;\">\u4e4b\u4e00<\/span><span style=\"color: #000000;\">\u662f\u6b8b\u5dee\u4e4b\u95f4\u4e0d\u5b58\u5728\u76f8\u5173\u6027\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u5047\u8bbe\u6b8b\u5dee\u662f\u72ec\u7acb\u7684\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u786e\u5b9a\u662f\u5426\u6ee1\u8db3\u6b64\u5047\u8bbe\u7684\u4e00\u79cd\u65b9\u6cd5\u662f\u6267\u884c<a href=\"https:\/\/statorials.org\/cn\/\u675c\u5bbe\u6c83\u68ee\u68c0\u9a8c\/\" target=\"_blank\" rel=\"noopener\">Durbin-Watson \u68c0\u9a8c<\/a>\uff0c\u8be5\u68c0\u9a8c\u7528\u4e8e\u68c0\u6d4b<a href=\"https:\/\/statorials.org\/cn\/\u7ebf\u6027\u56de\u5f52-python\/\" target=\"_blank\" rel=\"noopener\">\u56de\u5f52<\/a>\u6b8b\u5dee\u4e2d\u662f\u5426\u5b58\u5728\u81ea\u76f8\u5173\u3002\u8be5\u6d4b\u8bd5\u4f7f\u7528\u4ee5\u4e0b\u5047\u8bbe\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>H <sub>0<\/sub> \uff08\u96f6\u5047\u8bbe\uff09\uff1a<\/strong>\u6b8b\u5dee\u4e4b\u95f4\u4e0d\u5b58\u5728\u76f8\u5173\u6027\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>H <sub>A<\/sub> \uff08\u66ff\u4ee3\u5047\u8bbe\uff09\uff1a<\/strong>\u6b8b\u5dee\u662f\u81ea\u76f8\u5173\u7684\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u68c0\u9a8c\u7edf\u8ba1\u91cf\u7ea6\u7b49\u4e8e 2*(1-r)\uff0c\u5176\u4e2d r \u662f\u6b8b\u5dee\u7684\u6837\u672c\u81ea\u76f8\u5173\u3002\u56e0\u6b64\uff0c\u68c0\u9a8c\u7edf\u8ba1\u91cf\u5c06\u59cb\u7ec8\u4ecb\u4e8e 0 \u548c 4 \u4e4b\u95f4\uff0c\u89e3\u91ca\u5982\u4e0b\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u68c0\u9a8c\u7edf\u8ba1\u91cf\u4e3a<strong>2<\/strong>\u8868\u793a\u4e0d\u5b58\u5728\u5e8f\u5217\u76f8\u5173\u6027\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u68c0\u9a8c\u7edf\u8ba1\u91cf\u8d8a\u63a5\u8fd1<strong>0<\/strong> \uff0c\u5c31\u8d8a\u6709\u8bc1\u636e\u8868\u660e\u6b63\u5e8f\u5217\u76f8\u5173\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u68c0\u9a8c\u7edf\u8ba1\u91cf\u8d8a\u63a5\u8fd1<strong>4<\/strong> \uff0c\u8d1f\u5e8f\u5217\u76f8\u5173\u7684\u8bc1\u636e\u5c31\u8d8a\u591a\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u901a\u5e38\uff0c\u68c0\u9a8c\u7edf\u8ba1\u503c\u5728 1.5 \u5230 2.5 \u4e4b\u95f4\u88ab\u8ba4\u4e3a\u662f\u6b63\u5e38\u7684\u3002\u4f46\u662f\uff0c\u8d85\u51fa\u6b64\u8303\u56f4\u7684\u503c\u53ef\u80fd\u8868\u660e\u81ea\u76f8\u5173\u5b58\u5728\u95ee\u9898\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 Python \u4e2d\u6267\u884c Durbin-Watson \u6d4b\u8bd5\u3002<\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b\uff1aPython \u4e2d\u7684 Durbin-Watson \u6d4b\u8bd5<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u6570\u636e\u96c6\uff0c\u63cf\u8ff0\u4e86 10 \u540d\u7bee\u7403\u8fd0\u52a8\u5458\u7684\u5c5e\u6027\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">import<\/span> numpy <span style=\"color: #107d3f;\">as<\/span> np\n<span style=\"color: #107d3f;\">import<\/span> pandas <span style=\"color: #107d3f;\">as<\/span> pd\n\n<span style=\"color: #008080;\">#create dataset<\/span>\ndf = pd.DataFrame({'rating': [90, 85, 82, 88, 94, 90, 76, 75, 87, 86],\n                   'points': [25, 20, 14, 16, 27, 20, 12, 15, 14, 19],\n                   'assists': [5, 7, 7, 8, 5, 7, 6, 9, 9, 5],\n                   'rebounds': [11, 8, 10, 6, 6, 9, 6, 10, 10, 7]})\n\n<span style=\"color: #008080;\">#view dataset\n<\/span>df\n\n\trating points assists rebounds\n0 90 25 5 11\n1 85 20 7 8\n2 82 14 7 10\n3 88 16 8 6\n4 94 27 5 6\n5 90 20 7 9\n6 76 12 6 6\n7 75 15 9 10\n8 87 14 9 10\n9 86 19 5 7<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u4f7f\u7528<em>\u8bc4\u7ea7<\/em>\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\uff0c\u5176\u4ed6\u4e09\u4e2a\u53d8\u91cf\u4f5c\u4e3a\u9884\u6d4b\u53d8\u91cf\u6765\u62df\u5408\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">from<\/span> statsmodels.formula.api <span style=\"color: #107d3f;\">import<\/span> ols\n\n<span style=\"color: #008080;\">#fit multiple linear regression model\n<\/span>model = ols('rating ~ points + assists + rebounds', data=df). <span style=\"color: #3366ff;\">fit<\/span> ()\n\n<span style=\"color: #008080;\">#view model summary\n<\/span>print(model.summary())\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 statsmodels \u5e93\u4e2d\u7684<a href=\"https:\/\/www.statsmodels.org\/stable\/generated\/statsmodels.stats.stattools.durbin_watson.html\" target=\"_blank\" rel=\"noopener\">durbin_watson() \u51fd\u6570<\/a>\u6267\u884c Watson Durbin\uff0c\u4ee5\u786e\u5b9a\u56de\u5f52\u6a21\u578b\u6b8b\u5dee\u662f\u5426\u81ea\u76f8\u5173\uff1a<\/span><\/p>\n<pre style=\"background-color: #ececec; font-size: 15px;\"> <strong><span style=\"color: #107d3f;\">from<\/span> statsmodels.stats.stattools <span style=\"color: #107d3f;\">import<\/span> durbin_watson\n\n<span style=\"color: #008080;\">#perform Durbin-Watson test\n<\/span>durbin_watson(model.resid)\n\n2,392<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u68c0\u9a8c\u7edf\u8ba1\u91cf\u4e3a<strong>2.392<\/strong> \u3002\u7531\u4e8e\u8be5\u503c\u4ecb\u4e8e 1.5 \u548c 2.5 \u4e4b\u95f4\uff0c\u56e0\u6b64\u6211\u4eec\u8ba4\u4e3a\u81ea\u76f8\u5173\u5728\u6b64\u56de\u5f52\u6a21\u578b\u4e2d\u4e0d\u662f\u95ee\u9898\u3002<\/span><\/p>\n<h3><strong>\u5982\u4f55\u5904\u7406\u81ea\u76f8\u5173<\/strong><\/h3>\n<p><span style=\"color: #000000;\">\u5982\u679c\u60a8\u62d2\u7edd\u96f6\u5047\u8bbe\u5e76\u5f97\u51fa\u6b8b\u5dee\u4e2d\u5b58\u5728\u81ea\u76f8\u5173\u7684\u7ed3\u8bba\uff0c\u90a3\u4e48\u5982\u679c\u60a8\u8ba4\u4e3a\u95ee\u9898\u8db3\u591f\u4e25\u91cd\uff0c\u5219\u53ef\u4ee5\u901a\u8fc7\u591a\u79cd\u9009\u62e9\u6765\u7ea0\u6b63\u8be5\u95ee\u9898\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>1.<\/strong>\u5bf9\u4e8e\u6b63\u5e8f\u5217\u76f8\u5173\uff0c\u8bf7\u8003\u8651\u5c06\u56e0\u53d8\u91cf\u548c\/\u6216\u81ea\u53d8\u91cf\u7684\u6ede\u540e\u6dfb\u52a0\u5230\u6a21\u578b\u4e2d\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>2.<\/strong>\u5bf9\u4e8e\u8d1f\u5e8f\u5217\u76f8\u5173\uff0c\u8bf7\u786e\u4fdd\u6ca1\u6709\u4efb\u4f55\u53d8\u91cf<em>\u8fc7\u5ea6\u5ef6\u8fdf<\/em>\u3002<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>3.<\/strong>\u5bf9\u4e8e\u5b63\u8282\u6027\u76f8\u5173\u6027\uff0c\u8bf7\u8003\u8651\u5411\u6a21\u578b\u6dfb\u52a0\u5b63\u8282\u6027\u865a\u62df\u53d8\u91cf\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u7ebf\u6027\u56de\u5f52\u7684\u5047\u8bbe\u4e4b\u4e00\u662f\u6b8b\u5dee\u4e4b\u95f4\u4e0d\u5b58\u5728\u76f8\u5173\u6027\u3002\u6362\u53e5\u8bdd\u8bf4\uff0c\u5047\u8bbe\u6b8b\u5dee\u662f\u72ec\u7acb\u7684\u3002 \u786e\u5b9a\u662f\u5426\u6ee1\u8db3\u6b64\u5047\u8bbe\u7684\u4e00\u79cd\u65b9\u6cd5\u662f\u6267\u884cDu [&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-872","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\/ 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