{"id":456,"date":"2023-07-29T20:44:21","date_gmt":"2023-07-29T20:44:21","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e5%b0%86-gamma-%e5%88%86%e5%b8%83%e6%8b%9f%e5%90%88%e5%88%b0-r-%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e9%9b%86\/"},"modified":"2023-07-29T20:44:21","modified_gmt":"2023-07-29T20:44:21","slug":"%e5%b0%86-gamma-%e5%88%86%e5%b8%83%e6%8b%9f%e5%90%88%e5%88%b0-r-%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e9%9b%86","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e5%b0%86-gamma-%e5%88%86%e5%b8%83%e6%8b%9f%e5%90%88%e5%88%b0-r-%e4%b8%ad%e7%9a%84%e6%95%b0%e6%8d%ae%e9%9b%86\/","title":{"rendered":"\u5982\u4f55\u5c06\u4f3d\u739b\u5206\u5e03\u62df\u5408\u5230 r \u4e2d\u7684\u6570\u636e\u96c6"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5c06<strong>\u4f3d\u739b\u5206\u5e03<\/strong>\u62df\u5408\u5230 R \u4e2d\u7684\u6570\u636e\u96c6\u3002<\/span><\/p>\n<h2><strong><span style=\"color: #000000;\">\u5728 R \u4e2d\u62df\u5408\u4f3d\u739b\u5206\u5e03<\/span><\/strong><\/h2>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u60a8\u6709\u4e00\u4e2a\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u751f\u6210\u7684\u6570\u636e\u96c6<em>z<\/em> \uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#generate 50 random values that follow a gamma distribution with shape parameter = 3<\/span>\n<span style=\"color: #008080;\">#and shape parameter = 10 combined with some gaussian noise<\/span>\nz &lt;- rgamma(50, 3, 10) + rnorm(50, 0, .02)\n\n<span style=\"color: #008080;\">#view first 6 values<\/span>\nhead(z)\n[1] 0.07730 0.02495 0.12788 0.15011 0.08839 0.09941<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8981\u67e5\u770b\u4f3d\u9a6c\u5206\u5e03\u5bf9\u6570\u636e\u96c6<em>z<\/em>\u7684\u62df\u5408\u7a0b\u5ea6\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528 R \u4e2d\u7684<strong>fitdistrplus<\/strong>\u5305\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#install 'fitdistrplus' package if not already installed<\/span>\ninstall. <span style=\"color: #3366ff;\">packages<\/span> ('fitdistrplus')\n\n<span style=\"color: #008080;\">#load package<\/span>\nlibrary(fitdistrplus)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4f7f\u7528\u6b64\u5305\u6765\u8c03\u6574\u53d1\u884c\u7248\u7684\u4e00\u822c\u8bed\u6cd5\u662f\uff1a<\/span><\/p>\n<p> <strong><span style=\"color: #000000;\">fitdist(dataset, distr = \u201c\u60a8\u9009\u62e9\u7684\u5206\u5e03\u201d, method = \u201c\u60a8\u7684\u62df\u5408\u6570\u636e\u65b9\u6cd5\u201d)<\/span><\/strong><\/p>\n<p><span style=\"color: #000000;\">\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6211\u4eec\u5c06\u4f7f\u7528\u4f3d\u9a6c\u5206\u5e03\u548c\u6700\u5927\u4f3c\u7136\u4f30\u8ba1\u65b9\u6cd5\u6765\u62df\u5408\u4e4b\u524d\u751f\u6210\u7684<em>z<\/em>\u6570\u636e\u96c6\u6765\u62df\u5408\u6570\u636e\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#fit our dataset to a gamma distribution using mle<\/span>\nfit &lt;- fitdist(z, distr = \"gamma\", method = \"male\")\n\n<span style=\"color: #008080;\">#view the summary of the fit<\/span>\nsummary(fit)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8fd9\u4f1a\u4ea7\u751f\u4ee5\u4e0b\u7ed3\u679c\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\">\u7136\u540e\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\u751f\u6210\u56fe\u8868\u6765\u663e\u793a\u4f3d\u739b\u5206\u5e03\u5bf9\u6570\u636e\u96c6\u7684\u62df\u5408\u7a0b\u5ea6\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#produce plots<\/span>\nplot(fit)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8fd9\u4f1a\u4ea7\u751f\u4ee5\u4e0b\u56fe\uff1a<\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u662f\u6211\u4eec\u7528\u4e8e\u5c06\u4f3d\u739b\u5206\u5e03\u62df\u5408\u5230 R \u6570\u636e\u96c6\u7684\u5b8c\u6574\u4ee3\u7801\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#install 'fitdistrplus' package if not already installed\n<\/span>install. <span style=\"color: #3366ff;\">packages<\/span> ('fitdistrplus')\n\n<span style=\"color: #008080;\">#load package\n<\/span>library(fitdistrplus)\n\n<span style=\"color: #008080;\">#generate 50 random values that follow a gamma distribution with shape parameter = 3\n<\/span><span style=\"color: #008080;\">#and shape parameter = 10 combined with some gaussian noise\n<\/span>z &lt;- rgamma(50, 3, 10) + rnorm(50, 0, .02)\n\n<span style=\"color: #008080;\">#fit our dataset to a gamma distribution using mle\n<\/span>fit &lt;- fitdist(z, distr = \"gamma\", method = \"male\")\n\n<span style=\"color: #008080;\">#view the summary of the fit\n<\/span>summary(fit)\n\n<span style=\"color: #008080;\">#produce plots to visualize the fit\n<\/span>plot(fit)\n<\/strong><\/pre>\n","protected":false},"excerpt":{"rendered":"<p>\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5c06\u4f3d\u739b\u5206\u5e03\u62df\u5408\u5230 R \u4e2d\u7684\u6570\u636e\u96c6\u3002 \u5728 R \u4e2d\u62df\u5408\u4f3d\u739b\u5206\u5e03 \u5047\u8bbe\u60a8\u6709\u4e00\u4e2a\u4f7f\u7528\u4ee5\u4e0b\u65b9\u6cd5\u751f\u6210\u7684\u6570\u636e\u96c6 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