{"id":501,"date":"2023-07-29T16:49:12","date_gmt":"2023-07-29T16:49:12","guid":{"rendered":"https:\/\/statorials.org\/ja\/r%e3%81%ae%e3%82%a2%e3%83%95%e3%82%99%e3%83%a9%e3%82%a4%e3%83%b3\/"},"modified":"2023-07-29T16:49:12","modified_gmt":"2023-07-29T16:49:12","slug":"r%e3%81%ae%e3%82%a2%e3%83%95%e3%82%99%e3%83%a9%e3%82%a4%e3%83%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ja\/r%e3%81%ae%e3%82%a2%e3%83%95%e3%82%99%e3%83%a9%e3%82%a4%e3%83%b3\/","title":{"rendered":"R \u3067 aline() \u3092\u4f7f\u7528\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u306b\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5"},"content":{"rendered":"<p><\/p>\n<hr>\n<p><span style=\"color: #000000;\">R \u306e<strong>abline()<\/strong>\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001R \u306e\u30d7\u30ed\u30c3\u30c8\u306b 1 \u3064\u4ee5\u4e0a\u306e\u76f4\u7dda\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3053\u306e\u95a2\u6570\u306f\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/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\uff1a<\/span><\/p>\n<ul>\n<li> <span style=\"color: #000000;\"><strong>a\u3001b:<\/strong>\u7dda\u306e\u539f\u70b9\u3068\u50be\u304d\u3092\u6307\u5b9a\u3059\u308b\u4e00\u610f\u306e\u5024<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>h:<\/strong>\u6c34\u5e73\u7dda\u306e y \u5024<\/span><\/li>\n<li><span style=\"color: #000000;\"><strong>v:<\/strong>\u5782\u76f4\u7dda\u306e x \u5024<\/span><\/li>\n<\/ul>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u4f8b\u306f\u3001\u3053\u306e\u95a2\u6570\u3092\u5b9f\u969b\u306b\u4f7f\u7528\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/span><\/p>\n<h2><span style=\"color: #000000;\"><strong>\u6a2a\u7dda\u306e\u5165\u308c\u65b9<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">R \u306e\u30d7\u30ed\u30c3\u30c8\u306b\u6c34\u5e73\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u57fa\u672c\u30b3\u30fc\u30c9\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059: <strong>abline(h = some value)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u5185\u306e<em>x<\/em>\u3068<em>y<\/em>\u306e\u5024\u3092\u8868\u793a\u3059\u308b\u6b21\u306e\u6563\u5e03\u56f3\u304c\u3042\u308b\u3068\u3057\u307e\u3059\u3002<\/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;\">\u5024 y = 20 \u306b\u6c34\u5e73\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u306b\u306f\u3001\u6b21\u306e\u30b3\u30fc\u30c9\u3092\u4f7f\u7528\u3067\u304d\u307e\u3059\u3002<\/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;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001 <em>y<\/em>\u306e\u5e73\u5747\u5024\u306b\u6c34\u5e73\u5b9f\u7dda\u3092\u8ffd\u52a0\u3057\u3001\u5e73\u5747\u5024\u306e\u4e0a\u4e0b 1 \u6a19\u6e96\u504f\u5dee\u306e 2 \u672c\u306e\u6c34\u5e73\u70b9\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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>\u7e26\u7dda\u306e\u5165\u308c\u65b9<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">R \u306e\u30d7\u30ed\u30c3\u30c8\u306b\u5782\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u57fa\u672c\u30b3\u30fc\u30c9\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059: <strong>abline(v = some value)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u306e\u5e73\u5747\u5024\u306b\u5782\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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>\u56de\u5e30\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5<\/strong><\/span><\/h2>\n<p><span style=\"color: #000000;\">R \u306e\u30d7\u30ed\u30c3\u30c8\u306b\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u57fa\u672c\u30b3\u30fc\u30c9\u306f\u6b21\u306e\u3068\u304a\u308a\u3067\u3059: <strong>abline(model)<\/strong><\/span><\/p>\n<p><span style=\"color: #000000;\">\u6b21\u306e\u30b3\u30fc\u30c9\u306f\u3001\u8fd1\u4f3c\u7dda\u5f62\u56de\u5e30\u76f4\u7dda\u3092\u6563\u5e03\u56f3\u306b\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002<\/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$y, pch = 16)\n\n<span style=\"color: #008080;\">#fit a linear regression model to the data\n<\/span>reg_model &lt;- lm(y ~ x, data = data)\n\n<span style=\"color: #008080;\">#add the fitted regression line to the scatterplot\n<\/span>abline(reg_model, col=\"steelblue\")<\/strong><\/pre>\n<p> <span style=\"color: #000000;\">abline() \u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u5358\u7d14\u306a\u7dda\u5f62\u56de\u5e30\u76f4\u7dda\u3092\u30c7\u30fc\u30bf\u306b\u9069\u5408\u3055\u305b\u308b\u306b\u306f\u3001\u5207\u7247\u3068\u50be\u304d\u306e\u5024\u304c\u5fc5\u8981\u306a\u3060\u3051\u3067\u3042\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<p><span style=\"color: #000000;\">\u3057\u305f\u304c\u3063\u3066\u3001 <strong>abline()<\/strong>\u3092\u4f7f\u7528\u3057\u3066\u56de\u5e30\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u5225\u306e\u65b9\u6cd5\u306f\u3001\u56de\u5e30\u30e2\u30c7\u30eb\u306e\u5143\u306e\u4fc2\u6570\u3068\u50be\u304d\u4fc2\u6570\u3092\u660e\u793a\u7684\u306b\u6307\u5b9a\u3059\u308b\u3053\u3068\u3067\u3059\u3002<\/span><\/p>\n<pre style=\"background-color: #e5e5e5; font-size: 15px;\"> <strong><span style=\"color: #008080;\">#define dataset\n<\/span>data &lt;- data.frame(x = c(1, 1, 2, 3, 4, 4, 5, 6, 7, 7, 8, 9, 10, 11, 11),\n                   y = c(13, 14, 17, 12, 23, 24, 25, 25, 24, 28, 32, 33, 35, 40, 41))\n\n<span style=\"color: #008080;\">#create scatterplot of <em>x<\/em> and <em>y<\/em> values\n<\/span>plot(data$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;\">\u3053\u308c\u306b\u3088\u308a\u3001\u524d\u3068\u540c\u3058\u884c\u304c\u751f\u6210\u3055\u308c\u308b\u3053\u3068\u306b\u6ce8\u610f\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/span><\/p>\n<hr>\n<p> <span style=\"color: #000000;\"><a href=\"https:\/\/statorials.org\/ja\/-10\/\" target=\"_blank\" rel=\"noopener\">\u3053\u306e\u30da\u30fc\u30b8<\/a>\u3067\u306f\u3001\u305d\u306e\u4ed6\u306e R \u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3092\u898b\u3064\u3051\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>R \u306eabline()\u95a2\u6570\u3092\u4f7f\u7528\u3059\u308b\u3068\u3001R \u306e\u30d7\u30ed\u30c3\u30c8\u306b 1 \u3064\u4ee5\u4e0a\u306e\u76f4\u7dda\u3092\u8ffd\u52a0\u3067\u304d\u307e\u3059\u3002 \u3053\u306e\u95a2\u6570\u306f\u6b21\u306e\u69cb\u6587\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002 abline(a=NULL, b=NULL, h=NULL, v=NULL, \u2026) \u91d1\uff1a a\u3001 [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[],"class_list":["post-501","post","type-post","status-publish","format-standard","hentry","category-16"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>R \u3067 abline() \u3092\u4f7f\u7528\u3057\u3066\u30d7\u30ed\u30c3\u30c8\u306b\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5 - Statology<\/title>\n<meta name=\"description\" content=\"\u3053\u306e\u30c1\u30e5\u30fc\u30c8\u30ea\u30a2\u30eb\u3067\u306f\u3001R \u3067 abline() \u95a2\u6570\u3092\u4f7f\u7528\u3057\u3066\u3001R \u306e\u30d1\u30b9\u306b 1 \u3064\u4ee5\u4e0a\u306e\u76f4\u7dda\u3092\u8ffd\u52a0\u3059\u308b\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3059\u3002\" \/>\n<meta name=\"robots\" content=\"index, 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