{"id":479,"date":"2023-07-29T18:53:48","date_gmt":"2023-07-29T18:53:48","guid":{"rendered":"https:\/\/statorials.org\/cn\/%e6%8a%96%e5%8a%a8%e5%87%bd%e6%95%b0r\/"},"modified":"2023-07-29T18:53:48","modified_gmt":"2023-07-29T18:53:48","slug":"%e6%8a%96%e5%8a%a8%e5%87%bd%e6%95%b0r","status":"publish","type":"post","link":"https:\/\/statorials.org\/cn\/%e6%8a%96%e5%8a%a8%e5%87%bd%e6%95%b0r\/","title":{"rendered":"\u5982\u4f55\u4f7f\u7528r\u4e2d\u7684jitter\u51fd\u6570\u5904\u7406\u70b9\u4e91"},"content":{"rendered":"

<\/p>\n

\n

\u672c\u6559\u7a0b\u89e3\u91ca\u4e86\u4f55\u65f6\u4ee5\u53ca\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684\u6296\u52a8<\/strong>\u51fd\u6570\u6765\u5904\u7406\u70b9\u4e91\u3002<\/span><\/p>\n

\u4f55\u65f6\u4f7f\u7528\u6296\u52a8<\/strong><\/span><\/h3>\n

\u6563\u70b9\u56fe<\/strong>\u975e\u5e38\u9002\u5408\u53ef\u89c6\u5316\u4e24\u4e2a\u8fde\u7eed\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u4f8b\u5982\uff0c\u4ee5\u4e0b\u6563\u70b9\u56fe\u5e2e\u52a9\u6211\u4eec\u53ef\u89c6\u5316 100 \u540d\u8fd0\u52a8\u5458\u7684\u8eab\u9ad8\u548c\u4f53\u91cd\u4e4b\u95f4\u7684\u5173\u7cfb\uff1a<\/span><\/p>\n

 #define vectors of heights and weights\n<\/span>weights <- runif(100, 160, 240) \nheights <- (weights\/3) + rnorm(100)\n\n#create data frame of heights and weights\n<\/span>data <- as.data.frame(cbind(weights, heights))\n\n#view first six rows of data frame\n<\/span>head(data)\n\n# weights heights\n#1 170.8859 57.20745\n#2 183.2481 62.01162\n#3 235.6884 77.93126\n#4 231.9864 77.12520\n#5 200.8562 67.93486\n#6 169.6987 57.54977\n#create scatterplot of heights vs weights\n<\/span>plot(data$weights, data$heights, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u7136\u800c\uff0c\u6709\u65f6\u6211\u4eec\u53ef\u80fd\u60f3\u8981\u53ef\u89c6\u5316\u4e00\u4e2a\u8fde\u7eed\u53d8\u91cf\u548c\u53e6\u4e00\u4e2a\u63a5\u8fd1<\/em>\u8fde\u7eed\u53d8\u91cf\u4e4b\u95f4\u7684\u5173\u7cfb\u3002<\/span><\/p>\n
\u4f8b\u5982\uff0c\u5047\u8bbe\u6211\u4eec\u6709\u4ee5\u4e0b\u6570\u636e\u96c6\uff0c\u663e\u793a\u7bee\u7403\u8fd0\u52a8\u5458\u5728\u4e00\u4e2a\u8d5b\u5b63\u7684\u524d 10 \u573a\u6bd4\u8d5b\u4e2d\u9996\u53d1\u7684\u6bd4\u8d5b\u6570\u91cf\u4ee5\u53ca\u4ed6\u7684\u573a\u5747\u5f97\u5206\uff1a<\/span><\/p>\n
 #create data frame<\/span>\ngames_started <- sample(1:10, 300, TRUE)\npoints_per_game <- 3*games_started + rnorm(300)\ndata <- as.data.frame(cbind(games_started, points_per_game))\n\n#view first six rows of data frame\n<\/span>head(data)\n\n# games_started points_per_game\n#1 9 25.831554\n#2 9 26.673983\n#3 10 29.850948\n#4 4 12.024353\n#5 4 11.534192\n#6 1 4.383127<\/strong><\/pre>\n
\u6bcf\u573a\u6bd4\u8d5b\u7684\u5f97\u5206<\/em>\u662f\u8fde\u7eed\u53d8\u91cf\uff0c\u4f46\u6bd4\u8d5b\u5f00\u59cb<\/em>\u662f\u79bb\u6563\u53d8\u91cf\u3002\u5982\u679c\u6211\u4eec\u5c1d\u8bd5\u521b\u5efa\u8fd9\u4e24\u4e2a\u53d8\u91cf\u7684\u6563\u70b9\u56fe\uff0c\u5b83\u5c06\u5982\u4e0b\u6240\u793a\uff1a<\/span><\/p>\n
 #create scatterplot of games started vs average points per game\n<\/span>plot(data$games_started, data$points_per_game, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u4ece\u8fd9\u4e2a\u6563\u70b9\u56fe\u4e2d\uff0c\u6211\u4eec\u53ef\u4ee5\u8bf4\u6bd4\u8d5b\u5f00\u59cb\u6b21\u6570<\/em>\u548c\u6bcf\u573a\u6bd4\u8d5b\u7684\u5e73\u5747\u5f97\u5206\u4e4b\u95f4<\/em>\u5b58\u5728\u6b63\u76f8\u5173\u5173\u7cfb\uff0c\u4f46\u8981\u770b\u5230\u56fe\u4e2d\u7684\u5404\u4e2a\u70b9\u6709\u70b9\u56f0\u96be\uff0c\u56e0\u4e3a\u5176\u4e2d\u8bb8\u591a\u70b9\u91cd\u53e0\u3002<\/span><\/p>\n
\u4f7f\u7528Jitter<\/strong>\u51fd\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u5411\u629b\u51fa\u7684 X \u8f74\u53d8\u91cf\u96c6<\/em>\u6dfb\u52a0\u4e00\u4e9b\u201c\u566a\u58f0\u201d\uff0c\u4ee5\u4fbf\u6211\u4eec\u53ef\u4ee5\u66f4\u6e05\u695a\u5730\u770b\u5230\u7ed8\u56fe\u4e0a\u7684\u5404\u4e2a\u70b9\uff1a<\/span><\/p>\n
 #add jitter to games started\n<\/em><\/span>plot( jitter<\/span> (data$games_started), data$points_per_game, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u6211\u4eec\u53ef\u4ee5\u9009\u62e9\u5411\u6296\u52a8\u6dfb\u52a0\u4e00\u4e2a\u6570\u5b57\u53c2\u6570\uff0c\u4ee5\u5411\u6570\u636e\u6dfb\u52a0\u66f4\u591a\u566a\u58f0\uff1a<\/span><\/p>\n
 #add jitter to games started\n<\/em><\/span>plot( jitter<\/span> (data$games_started, 2<\/span> ), data$points_per_game, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u7136\u800c\uff0c\u6211\u4eec\u5fc5\u987b\u5c0f\u5fc3\u4e0d\u8981\u6dfb\u52a0\u592a\u591a\u6296\u52a8\uff0c\u56e0\u4e3a\u8fd9\u53ef\u80fd\u4f1a\u5bfc\u81f4\u539f\u59cb\u6570\u636e\u5931\u771f\u592a\u591a\uff1a<\/span><\/p>\n
 plot( jitter<\/span> (data$games_started, 20<\/span> ), data$points_per_game, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u6296\u52a8\u63d0\u4f9b\u4e86\u66f4\u597d\u7684\u6570\u636e\u89c6\u56fe<\/strong><\/span><\/h3>\n
\u5f53\u79bb\u6563\u53d8\u91cf\u7684\u67d0\u4e2a\u7ea7\u522b\u7684\u503c\u6bd4\u5176\u4ed6\u7ea7\u522b\u591a\u5f97\u591a\u65f6\uff0c\u4e0d\u7a33\u5b9a\u6027\u7279\u522b\u6709\u7528\u3002<\/span><\/p>\n
\u4f8b\u5982\uff0c\u5728\u4ee5\u4e0b\u6570\u636e\u96c6\u4e2d\uff0c\u6709 300 \u540d\u7bee\u7403\u8fd0\u52a8\u5458\u5728\u672c\u8d5b\u5b63\u7684\u524d 5 \u573a\u6bd4\u8d5b\u4e2d\u9996\u53d1\u4e86 2 \u573a\uff0c\u4f46\u53ea\u6709\u5927\u7ea6 100 \u540d\u7403\u5458\u9996\u53d1\u4e86 1\u30013\u30014 \u6216 5 \u573a\u6bd4\u8d5b\uff1a
<\/span><\/p>\n
 games_started <- sample(1:5, 100, TRUE)\npoints_per_game <- 3*games_started + rnorm(100)\ndata <- as.data.frame(cbind(games_started, points_per_game))\n\ngames_twos <- rep(2, 200)\npoints_twos <- 3*games_twos + rnorm(200)\ndata_twos <- as.data.frame(cbind(games_twos, points_twos))\nnames(data_twos) <- c('games_started', 'points_per_game')\n\nall_data <- rbind(data, data_twos)<\/strong><\/pre>\n
\u5f53\u6211\u4eec\u53ef\u89c6\u5316\u76f8\u5bf9\u4e8e\u573a\u5747\u5f97\u5206\u7684\u6bd4\u8d5b\u573a\u6570\u65f6\uff0c\u6211\u4eec\u53ef\u4ee5\u8bf4\u6709\u66f4\u591a\u7684\u7403\u5458\u6253\u4e86 2 \u573a\u6bd4\u8d5b\uff0c\u4f46\u5f88\u96be\u786e\u5207\u5730\u8bf4\u6709\u591a\u5c11\u5176\u4ed6\u4eba<\/em>\u6253\u4e86 2 \u573a\u6bd4\u8d5b\uff1a<\/span><\/p>\n
 plot(all_data$games_started, all_data$points_per_game, pch = 16, col = 'steelblue')<\/strong><\/pre>\n
\u7136\u800c\uff0c\u4e00\u65e6\u6211\u4eec\u5c06\u6296\u52a8\u6dfb\u52a0\u5230\u6e38\u620f\u5f00\u59cb<\/em>\u53d8\u91cf\u4e2d\uff0c\u6211\u4eec\u5c31\u53ef\u4ee5\u770b\u5230\u6709\u591a\u5c11\u5176\u4ed6\u73a9\u5bb6\u5f00\u59cb\u4e86 2 \u573a\u6e38\u620f\uff1a<\/span><\/p>\n
 plot( jitter<\/span> (all_data$games_started), all_data$points_per_game,\n     pch=16, col='steelblue')<\/strong><\/pre>\n
\u7a0d\u5fae\u589e\u52a0\u6296\u52a8\u91cf\u53ef\u4ee5\u66f4\u660e\u663e\u5730\u63ed\u793a\u8fd9\u79cd\u5dee\u5f02\uff1a<\/span><\/p>\n
 plot( jitter<\/span> (all_data$games_started, 1.5<\/span> ), all_data$points_per_game,\n     pch=16, col='steelblue')<\/strong><\/pre>\n
\n
\u4ec5\u7528\u4e8e\u53ef\u89c6\u5316\u7684\u6296\u52a8<\/strong><\/span><\/p>\n<\/h3>\n
\u5982\u524d\u6240\u8ff0\uff0c\u6296\u52a8\u4f1a\u5411\u6570\u636e\u6dfb\u52a0\u968f\u673a\u566a\u58f0\uff0c\u5f53\u6211\u4eec\u60f3\u8981\u5728\u70b9\u4e91\u4e2d\u53ef\u89c6\u5316\u6570\u636e\u65f6\uff0c\u8fd9\u4f1a\u5f88\u6709\u7528\u3002\u901a\u8fc7\u4f7f\u7528\u6296\u52a8\u51fd\u6570\uff0c\u6211\u4eec\u53ef\u4ee5\u66f4\u597d\u5730\u4e86\u89e3\u6570\u636e\u96c6\u4e2d\u4e24\u4e2a\u53d8\u91cf\u4e4b\u95f4\u7684\u771f\u5b9e\u6f5c\u5728\u5173\u7cfb\u3002<\/span><\/p>\n
\u7136\u800c\uff0c\u5f53\u4f7f\u7528\u56de\u5f52\u7b49\u7edf\u8ba1\u5206\u6790\u65f6\uff0c\u5411\u6570\u636e\u96c6\u4e2d\u7684\u53d8\u91cf\u6dfb\u52a0\u968f\u673a\u566a\u58f0\u662f\u6ca1\u6709\u610f\u4e49\u7684\uff0c\u56e0\u4e3a\u8fd9\u4f1a\u5f71\u54cd\u5206\u6790\u7ed3\u679c\u3002<\/span><\/p>\n
\u6240\u4ee5\u6296\u52a8\u4ec5\u7528\u4e8e\u6570\u636e\u53ef\u89c6\u5316\uff0c\u800c\u4e0d\u7528\u4e8e\u6570\u636e\u5206\u6790\u3002<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"
\u672c\u6559\u7a0b\u89e3\u91ca\u4e86\u4f55\u65f6\u4ee5\u53ca\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684\u6296\u52a8\u51fd\u6570\u6765\u5904\u7406\u70b9\u4e91\u3002 \u4f55\u65f6\u4f7f\u7528\u6296\u52a8 \u6563\u70b9\u56fe\u975e\u5e38\u9002\u5408\u53ef\u89c6\u5316\u4e24\u4e2a\u8fde\u7eed\u53d8\u91cf\u4e4b\u95f4 […]<\/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-479","post","type-post","status-publish","format-standard","hentry","category-11"],"yoast_head":"\n\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684 Jitter \u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe - Statorials<\/title>\n<meta name=\"description\" content=\"\u672c\u6559\u7a0b\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684\u6296\u52a8\u51fd\u6570\u6765\u751f\u6210\u66f4\u5bb9\u6613\u9605\u8bfb\u7684\u6563\u70b9\u56fe\u3002\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/statorials.org\/cn\/\u6296\u52a8\u51fd\u6570r\/\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u5982\u4f55\u4f7f\u7528 R \u4e2d\u7684 Jitter \u51fd\u6570\u7ed8\u5236\u6563\u70b9\u56fe - 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