{"id":504,"date":"2023-07-29T16:49:12","date_gmt":"2023-07-29T16:49:12","guid":{"rendered":"https:\/\/statorials.org\/cn\/r-%e4%b8%ad%e7%9a%84-abline\/"},"modified":"2023-07-29T16:49:12","modified_gmt":"2023-07-29T16:49:12","slug":"r-%e4%b8%ad%e7%9a%84-abline","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/r-%e4%b8%ad%e7%9a%84-abline\/","title":{"rendered":"\u5982\u4f55\u5728 r \u4e2d\u4f7f\u7528 aline() \u5411\u7ed8\u56fe\u6dfb\u52a0\u76f4\u7ebf"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">R \u4e2d\u7684<strong>abline()<\/strong>\u51fd\u6570\u53ef\u7528\u4e8e\u5411 R \u4e2d\u7684\u7ed8\u56fe\u6dfb\u52a0\u4e00\u6761\u6216\u591a\u6761\u76f4\u7ebf\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u8be5\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a<\/span><\/p>\n<p> <span style=\"color: #000000;\"><strong>abline(a=NULL, b=NULL, h=NULL, v=NULL, \u2026)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u91d1\u5b50\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>a\u3001b\uff1a<\/strong>\u6307\u5b9a\u7ebf\u7684\u539f\u70b9\u548c\u659c\u7387\u7684\u552f\u4e00\u503c<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>h\uff1a<\/strong>\u6c34\u5e73\u7ebf\u7684 y \u503c<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>v\uff1a<\/strong>\u5782\u76f4\u7ebf\u7684 x \u503c<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u793a\u4f8b\u5c55\u793a\u4e86\u5982\u4f55\u5728\u5b9e\u8df5\u4e2d\u4f7f\u7528\u6b64\u529f\u80fd\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u5982\u4f55\u6dfb\u52a0\u6c34\u5e73\u7ebf<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5728 R \u4e2d\u5411\u56fe\u4e2d\u6dfb\u52a0\u6c34\u5e73\u7ebf\u7684\u57fa\u672c\u4ee3\u7801\u662f\uff1a <strong>abline(h = some value)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u6563\u70b9\u56fe\uff0c\u663e\u793a\u6570\u636e\u96c6\u4e2d<em>x<\/em>\u548c<em>y<\/em>\u7684\u503c\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define dataset\n<\/span>data &lt;- data.frame(x = c(1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11),\n                   y = c(13, 14, 17, 12, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40, 41))\n\n<span style=\"color: #008080;\">#plot <em>x<\/em> and <em>y<\/em> values in dataset\n<\/span>plot(data$x, data$y, pch = 16)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8981\u5728\u503c y = 20 \u5904\u6dfb\u52a0\u6c34\u5e73\u7ebf\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong>abline(h = 20, col = 'coral2', lwd = 2)<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u8bf4\u660e\u4e86\u5982\u4f55\u5411<em>y<\/em>\u7684\u5e73\u5747\u503c\u6dfb\u52a0\u4e00\u6761\u6c34\u5e73\u5b9e\u7ebf\uff0c\u5e76\u5728\u5e73\u5747\u503c\u4e0a\u65b9\u548c\u4e0b\u65b9\u5404\u4e00\u4e2a\u6807\u51c6\u5dee\u5904\u6dfb\u52a0\u4e24\u6761\u6c34\u5e73\u865a\u7ebf\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#create scatterplot for <em>x<\/em> and <em>y<\/em><\/span>\nplot(data$x, data$y, pch = 16)\n\n<span style=\"color: #008080;\">#create horizontal line at mean value of <em>y<\/em>\n<\/span>abline(h = mean(data$y), lwd = 2)\n\n<span style=\"color: #008080;\">#create horizontal lines at one standard deviation above and below the mean value\n<\/span>abline(h = mean(data$y) + sd(data$y), col = 'steelblue', lwd = 3, lty = 2)\nabline(h = mean(data$y) - sd(data$y), col = 'steelblue', lwd = 3, lty = 2)<\/strong><\/pre>\n<h2><span style=\"color: #000000;\"><strong>\u5982\u4f55\u6dfb\u52a0\u5782\u76f4\u7ebf<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5728 R \u4e2d\u5411\u7ed8\u56fe\u6dfb\u52a0\u5782\u76f4\u7ebf\u7684\u57fa\u672c\u4ee3\u7801\u662f\uff1a <strong>abline(v = some value)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u5728\u76f4\u65b9\u56fe\u4e0a\u7684\u5e73\u5747\u503c\u4e0a\u6dfb\u52a0\u4e00\u6761\u5782\u76f4\u7ebf\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#make this example reproducible\n<\/span>set.seed(0)\n\n<span style=\"color: #008080;\">#create dataset with 1000 random values normally distributed with mean = 10, sd = 2\n<\/span>data &lt;- rnorm(1000, mean = 10, sd = 2)\n\n<span style=\"color: #008080;\">#create histogram of data values\n<\/span>hist(data, col = 'steelblue')\n\n<span style=\"color: #008080;\">#draw a vertical dashed line at the mean value\n<\/span>abline(v = mean(data), lwd = 3, lty = 2)<\/strong><\/pre>\n<h2><span style=\"color: #000000;\"><strong>\u5982\u4f55\u6dfb\u52a0\u56de\u5f52\u7ebf<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">\u5728 R \u4e2d\u5411\u56fe\u4e2d\u6dfb\u52a0\u7b80\u5355\u7ebf\u6027\u56de\u5f52\u7ebf\u7684\u57fa\u672c\u4ee3\u7801\u662f\uff1a <strong>abline(model)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u4ee5\u4e0b\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u5c06\u62df\u5408\u7ebf\u6027\u56de\u5f52\u7ebf\u6dfb\u52a0\u5230\u6563\u70b9\u56fe\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define dataset\n<\/span>data &lt;- data.frame(x = c(1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11),\n                   y = c(13, 14, 17, 12, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40, 41))\n\n<span style=\"color: #008080;\">#create scatterplot of <em>x<\/em> and <em>y<\/em> values\n<\/span>plot(data$x, data$y, pch = 16)\n\n<span style=\"color: #008080;\">#fit a linear regression model to the data\n<\/span>reg_model &lt;- lm(y ~ x, data = data)\n\n<span style=\"color: #008080;\">#add the fitted regression line to the scatterplot\n<\/span>abline(reg_model, col=\"steelblue\")<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u6211\u4eec\u53ea\u9700\u8981\u622a\u8ddd\u548c\u659c\u7387\u7684\u503c\uff0c\u5373\u53ef\u4f7f\u7528 abline() \u51fd\u6570\u5c06\u7b80\u5355\u7684\u7ebf\u6027\u56de\u5f52\u7ebf\u62df\u5408\u5230\u6570\u636e\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u56e0\u6b64\uff0c\u4f7f\u7528<strong>abline()<\/strong>\u6dfb\u52a0\u56de\u5f52\u7ebf\u7684\u53e6\u4e00\u79cd\u65b9\u6cd5\u662f\u663e\u5f0f\u6307\u5b9a\u56de\u5f52\u6a21\u578b\u7684\u539f\u59cb\u7cfb\u6570\u548c\u659c\u7387\u7cfb\u6570\uff1a<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define dataset\n<\/span>data &lt;- data.frame(x = c(1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11),\n                   y = c(13, 14, 17, 12, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40, 41))\n\n<span style=\"color: #008080;\">#create scatterplot of <em>x<\/em> and <em>y<\/em> values\n<\/span>plot(data$x, data$y, pch = 16)\n\n<span style=\"color: #008080;\">#fit a linear regression model to the data\n<\/span>reg_model &lt;- lm(y ~ x, data = data)\n\n<span style=\"color: #008080;\">#define intercept and slope values\n<\/span>a &lt;- coefficients(reg_model)[1] <span style=\"color: #008080;\">#intercept<\/span>\nb &lt;- coefficients(reg_model)[2] <span style=\"color: #008080;\">#slope<\/span>\n\n<span style=\"color: #008080;\">#add the fitted regression line to the scatterplot\n<\/span>abline(a=a, b=b, col=\"steelblue\")<\/strong><\/pre>\n<p><span style=\"color: #000000;\">\u8bf7\u6ce8\u610f\uff0c\u8fd9\u4f1a\u751f\u6210\u4e0e\u4e4b\u524d\u76f8\u540c\u7684\u884c\u3002<\/span><\/p>\n<hr>\n<p><span style=\"color: #000000;\">\u60a8\u53ef\u4ee5\u5728<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\/\" target=\"_blank\" rel=\"noopener\">\u6b64\u9875\u9762<\/a>\u4e0a\u627e\u5230\u66f4\u591a R \u6559\u7a0b\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>R \u4e2d\u7684abline()\u51fd\u6570\u53ef\u7528\u4e8e\u5411 R \u4e2d\u7684\u7ed8\u56fe\u6dfb\u52a0\u4e00\u6761\u6216\u591a\u6761\u76f4\u7ebf\u3002 \u8be5\u51fd\u6570\u4f7f\u7528\u4ee5\u4e0b\u8bed\u6cd5\uff1a abline(a [&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-504","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"<!-- This site is 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