{"id":492,"date":"2023-07-29T17:48:18","date_gmt":"2023-07-29T17:48:18","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e9%80%90%e6%ad%a5%e5%9b%9e%e5%bd%92-r\/"},"modified":"2023-07-29T17:48:18","modified_gmt":"2023-07-29T17:48:18","slug":"%e9%80%90%e6%ad%a5%e5%9b%9e%e5%bd%92-r","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e9%80%90%e6%ad%a5%e5%9b%9e%e5%bd%92-r\/","title":{"rendered":"R \u4e2d\u9010\u6b65\u56de\u5f52\u7684\u5b8c\u6574\u6307\u5357"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/cn\/\u9636\u6bb5\u6027\u9009\u62d4\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u9010\u6b65\u56de\u5f52<\/a>\u662f\u4e00\u4e2a\u8fc7\u7a0b\uff0c\u6211\u4eec\u53ef\u4ee5\u7528\u5b83\u6765\u4ece\u4e00\u7ec4\u9884\u6d4b\u53d8\u91cf\u6784\u5efa<a href=\"https:\/\/statorials.org\/cn\/\u591a\u5143\u7ebf\u6027\u56de\u5f52-1\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u56de\u5f52\u6a21\u578b<\/a>\uff0c\u65b9\u6cd5\u662f\u5728\u6a21\u578b\u4e2d\u9010\u6b65\u8f93\u5165\u548c\u5220\u9664\u9884\u6d4b\u53d8\u91cf\uff0c\u76f4\u5230\u4e0d\u518d\u6709\u7edf\u8ba1\u5b66\u4e0a\u6709\u6548\u7684\u7406\u7531\u6765\u8f93\u5165\u6216\u5220\u9664\u9884\u6d4b\u53d8\u91cf\u3002\u5220\u9664\u66f4\u591a\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u9010\u6b65\u56de\u5f52\u7684\u76ee\u6807\u662f\u521b\u5efa\u4e00\u4e2a\u56de\u5f52\u6a21\u578b\uff0c\u5176\u4e2d\u5305\u62ec\u4e0e<a href=\"https:\/\/statorials.org\/cn\/\u53d8\u91cf\u89e3\u91ca\u6027\u53cd\u5e94\/\" target=\"_blank\" rel=\"noopener noreferrer\">\u54cd\u5e94\u53d8\u91cf<\/a>\u5728\u7edf\u8ba1\u4e0a\u663e\u7740\u76f8\u5173\u7684\u6240\u6709\u9884\u6d4b\u53d8\u91cf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u8bf4\u660e\u5982\u4f55\u5728 R \u4e2d\u6267\u884c\u4ee5\u4e0b\u9010\u6b65\u56de\u5f52\u8fc7\u7a0b\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u4e00\u6b65\u6b65\u5411\u524d\u9009\u62e9<\/span><\/li>\n<li><span style=\"color: #000000;\">\u9010\u6b65\u5411\u540e\u9009\u62e9<\/span><\/li>\n<li><span style=\"color: #000000;\">\u53cc\u5411\u9010\u6b65\u9009\u62e9<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u5bf9\u4e8e\u6bcf\u4e2a\u793a\u4f8b\uff0c\u6211\u4eec\u5c06\u4f7f\u7528\u5185\u7f6e\u7684<strong>mtcars<\/strong>\u6570\u636e\u96c6\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#view first six rows of <em>mtcars\n<\/em><\/span>head(mtcars)\n\n                   mpg cyl disp hp drat wt qsec vs am gear carb\nMazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4\nMazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4\nDatsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1\nHornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1\nHornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2\nValiant 18.1 6 225 105 2.76 3,460 20.22 1 0 3 1\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u6211\u4eec\u5c06\u4f7f\u7528<em>mpg<\/em> \uff08\u82f1\u91cc\/\u52a0\u4ed1\uff09\u4f5c\u4e3a\u54cd\u5e94\u53d8\u91cf\uff0c\u5e76\u4f7f\u7528\u6570\u636e\u96c6\u4e2d\u7684\u5176\u4ed6 10 \u4e2a\u53d8\u91cf\u4f5c\u4e3a\u6f5c\u5728\u7684\u9884\u6d4b\u53d8\u91cf\u6765\u62df\u5408\u591a\u5143\u7ebf\u6027\u56de\u5f52\u6a21\u578b\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u5bf9\u4e8e\u6bcf\u4e2a\u793a\u4f8b\uff0c\u6211\u4eec\u5c06\u4f7f\u7528 stats \u5305\u7684\u5185\u7f6e<a href=\"https:\/\/www.rdocumentation.org\/packages\/stats\/versions\/3.6.2\/topics\/step\" target=\"_blank\" rel=\"noopener noreferrer\">step()<\/a>\u51fd\u6570\u6765\u6267\u884c\u9010\u6b65\u9009\u62e9\uff0c\u8be5\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<p style=\"text-align: left;\"><span style=\"color: #000000;\"><strong>\u9636\u6bb5\uff08\u4ec5\u9650\u62e6\u622a\u6a21\u578b\u3001\u65b9\u5411\u3001\u8303\u56f4\uff09<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\"><strong>\u4ec5\u539f\u59cb\u6a21\u578b<\/strong>\uff1a\u4ec5\u539f\u59cb\u6a21\u578b\u7684\u516c\u5f0f<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u65b9\u5411\uff1a<\/strong>\u6b65\u8fdb\u641c\u7d22\u6a21\u5f0f\u53ef\u4ee5\u662f\u201c\u53cc\u5411\u201d\u3001\u201c\u5411\u540e\u201d\u6216\u201c\u5411\u524d\u201d\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>\u8303\u56f4\uff1a<\/strong>\u6307\u5b9a\u6211\u4eec\u60f3\u8981\u5c1d\u8bd5\u8f93\u5165\u6a21\u578b\u7684\u9884\u6d4b\u53d8\u91cf\u7684\u516c\u5f0f<\/span><\/li>\n<\/ul>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b1\uff1a\u9010\u6b65\u524d\u5411\u9009\u62e9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u9010\u6b65\u6267\u884c\u9009\u62e9\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define intercept-only model\n<\/span>intercept_only &lt;- lm(mpg ~ 1, data=mtcars)\n\n<span style=\"color: #008080;\">#define model with all predictors\n<\/span>all &lt;- lm(mpg ~ ., data=mtcars)\n\n<span style=\"color: #008080;\">#perform forward stepwise regression\n<\/span>forward &lt;- step(intercept_only, direction=' <span style=\"color: #008000;\">forward<\/span> ', scope= <span style=\"color: #3366ff;\">formula<\/span> (all), trace=0)\n\n<span style=\"color: #008080;\">#view results of forward stepwise regression<\/span>\nforward$anova\n\n   Step Df Deviance Resid. Df Resid. Dev AIC\n1 NA NA 31 1126.0472 115.94345\n2 + wt -1 847.72525 30 278.3219 73.21736\n3 + cyl -1 87.14997 29 191.1720 63.19800\n4 + hp -1 14.55145 28 176.6205 62.66456\n\n<span style=\"color: #008080;\">#view final model\n<\/span>forward$coefficients\n\n(Intercept) wt cyl hp \n 38.7517874 -3.1669731 -0.9416168 -0.0180381 \n<\/strong><\/pre>\n<p><span style=\"color: #000000;\"><em><strong>\u6ce8\u610f\uff1a<\/strong> trace=0 \u53c2\u6570\u544a\u8bc9 R \u4e0d\u8981\u663e\u793a\u9010\u6b65\u9009\u62e9\u7684\u5b8c\u6574\u7ed3\u679c\u3002\u5982\u679c\u5b58\u5728\u5927\u91cf\u9884\u6d4b\u53d8\u91cf\uff0c\u8fd9\u53ef\u80fd\u4f1a\u5360\u7528\u5927\u91cf\u7a7a\u95f4\u3002<\/em><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u5982\u4f55\u89e3\u91ca\u7ed3\u679c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u62df\u5408\u4ec5\u622a\u8ddd\u6a21\u578b\u3002\u8be5\u6a21\u578b\u7684 AIC \u4e3a<strong>115.94345<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7136\u540e\u6211\u4eec\u5c06\u6240\u6709\u53ef\u80fd\u7684\u6a21\u578b\u62df\u5408\u5230\u9884\u6d4b\u5668\u3002\u4e0e\u4f7f\u7528<em>wt<\/em>\u9884\u6d4b\u5668\u7684\u4ec5\u57fa\u7ebf\u6a21\u578b\u76f8\u6bd4\uff0c\u4ea7\u751f\u6700\u4f4e AIC \u4e14 AIC \u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u964d\u4f4e\u7684\u6a21\u578b\u3002\u8be5\u6a21\u578b\u7684 AIC \u4e3a<strong>73.21736<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u7528\u4e24\u4e2a\u9884\u6d4b\u53d8\u91cf\u62df\u5408\u6240\u6709\u53ef\u80fd\u7684\u6a21\u578b\u3002\u4e0e\u6dfb\u52a0\u4e86<em>cyl<\/em>\u9884\u6d4b\u5668\u7684\u5355\u9884\u6d4b\u5668\u6a21\u578b\u76f8\u6bd4\uff0c\u4ea7\u751f\u6700\u4f4e AIC \u4e14 AIC \u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u964d\u4f4e\u7684\u6a21\u578b\u3002\u8be5\u6a21\u578b\u7684 AIC \u4e3a<strong>63.19800<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u6240\u6709\u53ef\u80fd\u7684\u6a21\u578b\u62df\u5408\u5230\u4e09\u4e2a\u9884\u6d4b\u53d8\u91cf\u3002\u4e0e\u6dfb\u52a0\u4e86<em>hp<\/em>\u9884\u6d4b\u5668\u7684\u53cc\u9884\u6d4b\u5668\u6a21\u578b\u76f8\u6bd4\uff0c\u4ea7\u751f\u6700\u4f4e AIC \u4e14 AIC \u5177\u6709\u7edf\u8ba1\u663e\u7740\u6027\u964d\u4f4e\u7684\u6a21\u578b\u3002\u8be5\u6a21\u578b\u7684 AIC \u4e3a<strong>62.66456<\/strong> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u5c06\u6240\u6709\u53ef\u80fd\u7684\u6a21\u578b\u62df\u5408\u5230\u56db\u4e2a\u9884\u6d4b\u53d8\u91cf\u3002\u4e8b\u5b9e\u8bc1\u660e\uff0c\u8fd9\u4e9b\u6a21\u578b\u90fd\u6ca1\u6709\u663e\u7740\u964d\u4f4e AIC\uff0c\u56e0\u6b64\u6211\u4eec\u505c\u6b62\u4e86\u8be5\u8fc7\u7a0b\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6700\u7ec8\u6a21\u578b\u5982\u4e0b\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>mpg ~ 38.75 \u2013 3.17*\u91cd\u91cf \u2013 0.94*\u6c7d\u7f38 \u2013 0.02*hyp<\/strong><\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b2\uff1a\u9010\u6b65\u5411\u540e\u9009\u62e9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4e0b\u9762\u7684\u4ee3\u7801\u5c55\u793a\u4e86\u5982\u4f55\u540e\u9000\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define intercept-only model\n<\/span>intercept_only &lt;- lm(mpg ~ 1, data=mtcars)\n\n<span style=\"color: #008080;\">#define model with all predictors\n<\/span>all &lt;- lm(mpg ~ ., data=mtcars)\n\n<span style=\"color: #008080;\">#perform backward stepwise regression\n<\/span>backward &lt;- step(all, direction=' <span style=\"color: #008000;\">backward<\/span> ', scope= <span style=\"color: #3366ff;\">formula<\/span> (all), trace=0)\n\n<span style=\"color: #008080;\">#view results of backward stepwise regression<\/span>\nbackward$anova\n\n    Step Df Deviance Resid. Df Resid. Dev AIC\n1 NA NA 21 147.4944 70.89774\n2 - cyl 1 0.07987121 22 147.5743 68.91507\n3 - vs 1 0.26852280 23 147.8428 66.97324\n4 - carb 1 0.68546077 24 148.5283 65.12126\n5 - gear 1 1.56497053 25 150.0933 63.45667\n6 - drat 1 3.34455117 26 153.4378 62.16190\n7 - available 1 6.62865369 27 160.0665 61.51530\n8 - hp 1 9.21946935 28 169.2859 61.30730\n\n<span style=\"color: #008080;\">#view final model\n<\/span>backward$coefficients\n\n(Intercept) wt qsec am \n   9.617781 -3.916504 1.225886 2.935837\n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u5982\u4f55\u89e3\u91ca\u7ed3\u679c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u4f7f\u7528\u6240\u6709<em>p \u4e2a<\/em>\u9884\u6d4b\u53d8\u91cf\u62df\u5408\u6a21\u578b\u3002\u5c06\u5176\u5b9a\u4e49\u4e3a M <sub>p<\/sub> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u7136\u540e\uff0c\u5bf9\u4e8e k = p, p-1,\u20261\uff0c\u6211\u4eec\u62df\u5408\u5305\u542b M <sub>k<\/sub>\u4e2d\u9664\u4e00\u4e2a\u9884\u6d4b\u53d8\u91cf\u4e4b\u5916\u7684\u6240\u6709\u9884\u6d4b\u53d8\u91cf\u7684\u6240\u6709 k \u4e2a\u6a21\u578b\uff0c\u603b\u5171 k-1 \u4e2a\u9884\u6d4b\u53d8\u91cf\u3002\u7136\u540e\u4ece\u8fd9 k \u4e2a\u6a21\u578b\u4e2d\u9009\u62e9\u6700\u597d\u7684\u4e00\u4e2a\uff0c\u5e76\u5c06\u5176\u79f0\u4e3a M <sub>k-1<\/sub> \u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6700\u540e\uff0c\u6211\u4eec\u4f7f\u7528 AIC \u4ece M <sub>0<\/sub> \u2026 M <sub>p<\/sub>\u4e2d\u9009\u62e9\u6700\u4f73\u6a21\u578b\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6700\u7ec8\u6a21\u578b\u5982\u4e0b\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u82f1\u91cc\/\u52a0\u4ed1 ~ 9.62 \u2013 3.92*\u4f53\u91cd + 1.23*qsec + 2.94*\u4e0a\u5348<\/strong><\/span><\/p>\n<h3><span style=\"color: #000000;\"><strong>\u793a\u4f8b 3\uff1a\u53cc\u5411\u9010\u6b65\u9009\u62e9<\/strong><\/span><\/h3>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u663e\u793a\u4e86\u5982\u4f55\u5728\u4e24\u4e2a\u65b9\u5411\u4e0a\u6267\u884c\u9010\u6b65\u9009\u62e9\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define intercept-only model\n<\/span>intercept_only &lt;- lm(mpg ~ 1, data=mtcars)\n\n<span style=\"color: #008080;\">#define model with all predictors\n<\/span>all &lt;- lm(mpg ~ ., data=mtcars)\n\n<span style=\"color: #008080;\">#perform backward stepwise regression\n<\/span>both &lt;- step(intercept_only, direction=' <span style=\"color: #008000;\">both<\/span> ', scope= <span style=\"color: #3366ff;\">formula<\/span> (all), trace=0)\n\n<span style=\"color: #008080;\">#view results of backward stepwise regression<\/span>\nboth$anova\n\n   Step Df Deviance Resid. Df Resid. Dev AIC\n1 NA NA 31 1126.0472 115.94345\n2 + wt -1 847.72525 30 278.3219 73.21736\n3 + cyl -1 87.14997 29 191.1720 63.19800\n4 + hp -1 14.55145 28 176.6205 62.66456\n\n<span style=\"color: #008080;\">#view final model\n<\/span>both$coefficients\n\n(Intercept) wt cyl hp \n 38.7517874 -3.1669731 -0.9416168 -0.0180381 \n<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u5982\u4f55\u89e3\u91ca\u7ed3\u679c\uff1a<\/span><\/p>\n<ul>\n<li><span style=\"color: #000000;\">\u9996\u5148\uff0c\u6211\u4eec\u62df\u5408\u4ec5\u622a\u8ddd\u6a21\u578b\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u6309\u987a\u5e8f\u5411\u6a21\u578b\u6dfb\u52a0\u9884\u6d4b\u53d8\u91cf\uff0c\u5c31\u50cf\u6211\u4eec\u5bf9\u9010\u6b65\u9009\u62e9\u6240\u505a\u7684\u90a3\u6837\u3002\u7136\u800c\uff0c\u5728\u6dfb\u52a0\u6bcf\u4e2a\u9884\u6d4b\u53d8\u91cf\u540e\uff0c\u6211\u4eec\u8fd8\u5220\u9664\u4e86\u4e0d\u518d\u63d0\u4f9b\u6a21\u578b\u62df\u5408\u6539\u8fdb\u7684\u4efb\u4f55\u9884\u6d4b\u53d8\u91cf\u3002<\/span><\/li>\n<li><span style=\"color: #000000;\">\u6211\u4eec\u91cd\u590d\u8fd9\u4e2a\u8fc7\u7a0b\uff0c\u76f4\u5230\u5f97\u5230\u6700\u7ec8\u6a21\u578b\u3002<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6700\u7ec8\u6a21\u578b\u5982\u4e0b\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\"><strong>\u82f1\u91cc\/\u52a0\u4ed1 ~ 9.62 \u2013 3.92*\u4f53\u91cd + 1.23*qsec + 2.94*\u4e0a\u5348<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u524d\u5411\u6b65\u9aa4\u9009\u62e9\u548c\u4e24\u4e2a\u65b9\u5411\u7684\u6b65\u9aa4\u9009\u62e9\u4ea7\u751f\u76f8\u540c\u7684\u6700\u7ec8\u6a21\u5f0f\uff0c\u800c\u540e\u5411\u6b65\u9aa4\u9009\u62e9\u4ea7\u751f\u4e0d\u540c\u7684\u6a21\u5f0f\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\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\">\u5982\u4f55\u6d4b\u8bd5\u56de\u5f52\u659c\u7387\u7684\u663e\u7740\u6027<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\">\u5982\u4f55\u9605\u8bfb\u548c\u89e3\u91ca\u56de\u5f52\u8868<\/a><br \/><a href=\"https:\/\/statorials.org\/cn\/\u7edf\u8ba1\u5b66\u4ee5\u7b80\u5355\u76f4\u63a5\u7684\u65b9\u5f0f\u89e3\u91ca\u6982\u5ff5\uff0c\u6211\u4eec\u4f7f\u5b66\u4e60\u7edf\u8ba1\u53d8\u5f97\u66f4\u5bb9\u6613\/\">\u56de\u5f52\u4e2d\u7684\u591a\u91cd\u5171\u7ebf\u6027\u6307\u5357<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u9010\u6b65\u56de\u5f52\u662f\u4e00\u4e2a\u8fc7\u7a0b\uff0c\u6211\u4eec\u53ef\u4ee5\u7528\u5b83\u6765\u4ece\u4e00\u7ec4\u9884\u6d4b\u53d8\u91cf\u6784\u5efa\u56de\u5f52\u6a21\u578b\uff0c\u65b9\u6cd5\u662f\u5728\u6a21\u578b\u4e2d\u9010\u6b65\u8f93\u5165\u548c\u5220\u9664\u9884\u6d4b\u53d8\u91cf\uff0c\u76f4\u5230\u4e0d\u518d\u6709 [&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-492","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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