\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 R \u4e2d\u7ed8\u5236\u6570\u636e\u96c6\u7684\u7f6e\u4fe1\u533a\u95f4\u3002<\/span><\/p>\n \u5047\u8bbe\u6211\u4eec\u5728 R \u4e2d\u6709\u4ee5\u4e0b\u6570\u636e\u96c6\uff0c\u5305\u542b 100 \u884c\u548c 2 \u5217\uff1a<\/span><\/p>\n \u8981\u521b\u5efa x \u548c y \u4e4b\u95f4\u7684\u5173\u7cfb\u56fe\uff0c\u6211\u4eec\u53ef\u4ee5\u9996\u5148\u62df\u5408\u7ebf\u6027\u56de\u5f52\u6a21\u578b\uff1a<\/span><\/p>\n \u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528abline()<\/a>\u51fd\u6570\u548clines() \u51fd\u6570\u521b\u5efa\u4f30\u8ba1\u7684\u7ebf\u6027\u56de\u5f52\u7ebf\u56fe\uff0c\u4ee5\u521b\u5efa\u5b9e\u9645\u7684\u7f6e\u4fe1\u5e26\uff1a<\/span> <\/p>\n \u9ed1\u7ebf\u663e\u793a\u62df\u5408\u7684\u7ebf\u6027\u56de\u5f52\u7ebf\uff0c\u800c\u4e24\u6761\u84dd\u8272\u865a\u7ebf\u663e\u793a\u7f6e\u4fe1\u533a\u95f4\u3002<\/span><\/p>\n \u6216\u8005\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528\u4ee5\u4e0b\u4ee3\u7801\u586b\u5145\u7f6e\u4fe1\u533a\u95f4\u7ebf\u548c\u4f30\u8ba1\u7ebf\u6027\u56de\u5f52\u7ebf\u4e4b\u95f4\u7684\u533a\u57df\uff1a<\/span> <\/p>\n \u8fd9\u662f\u4ece\u5f00\u59cb\u5230\u7ed3\u675f\u7684\u5b8c\u6574\u4ee3\u7801\uff1a<\/span><\/p>\n \u4ec0\u4e48\u662f\u7f6e\u4fe1\u533a\u95f4\uff1f<\/a> \u7f6e\u4fe1\u533a\u95f4\u662f\u53ef\u80fd\u5305\u542b\u5177\u6709\u4e00\u5b9a\u7f6e\u4fe1\u6c34\u5e73\u7684\u603b\u4f53\u53c2\u6570\u7684\u503c\u8303\u56f4\u3002 \u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u5728 R \u4e2d\u7ed8\u5236\u6570\u636e\u96c6\u7684\u7f6e\u4fe1\u533a\u95f4\u3002 \u793a\u4f8b\uff1a […]<\/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-940","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u793a\u4f8b\uff1a\u5728 R \u4e2d\u7ed8\u5236\u7f6e\u4fe1\u533a\u95f4<\/strong><\/h3>\n
#make this example reproducible<\/span>\nset.seed(0)\n\n#create dataset<\/span>\nx <- rnorm(100)\ny <- x*2 + rnorm(100)\ndf <- data.frame(x = x, y = y)\n\n#view first six rows of dataset<\/span>\nhead(df)\n\n xy\n1 1.2629543 3.3077678\n2 -0.3262334 -1.4292433\n3 1.3297993 2.0436086\n4 1.2724293 2.5914389\n5 0.4146414 -0.3011029\n6 -1.5399500 -2.5031813\n<\/strong><\/pre>\n model <- lm(y ~ x, data = df)\n<\/strong><\/pre>\n
#get predicted y values using regression equation<\/span>\nnewx <- seq(min(df$x), max(df$x), length.out=100)\npreds <- predict(model, newdata = data.frame(x=newx), interval = 'confidence')\n\n#create plot of x vs. y, but don't display individual points (type='n')<\/span> \nplot(y ~ x, data = df, type = 'n')\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong> <\/pre>\n![\"\u5728](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/plotconfintr1.png\")
<\/p>\n #create plot of x vs. y<\/span>\nplot(y ~ x, data = df, type = 'n')\n\n#fill in area between regression line and confidence interval\npolygon(c(rev(newx), newx), c(rev(preds[,3]), preds[,2]), col = 'grey', border = NA)<\/span>\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong> <\/pre>\n![\"R](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/plotconfintr2.png\")
<\/p>\n #make this example reproducible\nset.seed(0)<\/span>\n\n#create dataset\nx <- rnorm(100)<\/span>\ny <- x*2 + rnorm(100)<\/span>\ndf <- data.frame(x = x, y = y)<\/span>\n\n#fit linear regression model\nmodel <- lm(y ~ x, data = df)<\/span>\n\n#get predicted y values using regression equation\nnewx <- seq(min(df$x), max(df$x), length.out=100)<\/span>\npreds <- predict(model, newdata = data.frame(x=newx), interval = 'confidence')<\/span>\n\n#create plot of x vs. y<\/span>\nplot(y ~ x, data = df, type = 'n')\n\n#fill in area between regression line and confidence interval\npolygon(c(rev(newx), newx), c(rev(preds[,3]), preds[,2]), col = 'grey', border = NA)<\/span>\n\n#add fitted regression line<\/span>\nabline(model)\n\n#add dashed lines for confidence bands\n<\/span>lines(newx, preds[,3], lty = 'dashed', col = 'blue')\nlines(newx, preds[,2], lty = 'dashed', col = 'blue')<\/strong><\/pre>\n\u5176\u4ed6\u8d44\u6e90<\/strong><\/span><\/h3>\n
\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684 abline() \u51fd\u6570\u5411\u7ed8\u56fe\u6dfb\u52a0\u76f4\u7ebf<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"