{"id":1606,"date":"2023-07-25T16:27:13","date_gmt":"2023-07-25T16:27:13","guid":{"rendered":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a1%e1%86%bc%e1%84%85%e1%85%a7%e1%86%a8%e1%84%92%e1%85%a1%e1%86%ab-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1\/"},"modified":"2023-07-25T16:27:13","modified_gmt":"2023-07-25T16:27:13","slug":"r%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a1%e1%86%bc%e1%84%85%e1%85%a7%e1%86%a8%e1%84%92%e1%85%a1%e1%86%ab-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/r%e1%84%8b%e1%85%b4-%e1%84%80%e1%85%a1%e1%86%bc%e1%84%85%e1%85%a7%e1%86%a8%e1%84%92%e1%85%a1%e1%86%ab-%e1%84%92%e1%85%ac%e1%84%80%e1%85%b1\/","title":{"rendered":"R\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95(\ub2e8\uacc4\ubcc4)"},"content":{"rendered":"

<\/p>\n

\n

\uac15\ub825\ud55c \ud68c\uadc0\ub294<\/strong> \uc791\uc5c5 \uc911\uc778 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uc774\uc0c1\uce58\ub098 \uc601\ud5a5\ub825 \uc788\ub294 \uad00\uce21\uce58\uac00<\/a> \uc788\uc744 \ub54c \uc77c\ubc18 \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0\uc758 \ub300\uc548\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4.<\/span><\/p>\n

R\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 MASS<\/strong> \ud328\ud0a4\uc9c0\uc758 rlm()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

\ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\ub294 \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud574 R\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n

1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131<\/strong><\/span><\/h3>\n

\uba3c\uc800 \uc791\uc5c5\ud560 \uac00\uc9dc \ub370\uc774\ud130\uc138\ud2b8\ub97c \ub9cc\ub4e4\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n

 #create data<\/span>\ndf <- data. frame<\/span> (x1=c(1, 3, 3, 4, 4, 6, 6, 8, 9, 3,\n                      11, 16, 16, 18, 19, 20, 23, 23, 24, 25),\n                 x2=c(7, 7, 4, 29, 13, 34, 17, 19, 20, 12,\n                      25, 26, 26, 26, 27, 29, 30, 31, 31, 32),\n                  y=c(17, 170, 19, 194, 24, 2, 25, 29, 30, 32,\n                      44, 60, 61, 63, 63, 64, 61, 67, 59, 70))\n\n#view first six rows of data\n<\/span>head(df)\n\n  x1 x2 y\n1 1 7 17\n2 3 7 170\n3 3 4 19\n4 4 29 194\n5 4 13 24\n6 6 34 2\n<\/strong><\/pre>\n
 2\ub2e8\uacc4: \uc77c\ubc18 \ucd5c\uc18c\uc81c\uacf1 \ud68c\uadc0 \uc218\ud589<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c\uc73c\ub85c, \uc77c\ubc18 \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0 \ubaa8\ub378\uc744 \ud53c\ud305\ud558\uace0 \ud45c\uc900\ud654\ub41c \uc794\ucc28<\/a> \uc758 \ud50c\ub86f\uc744 \ub9cc\ub4e4\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc2e4\uc81c\ub85c\ub294 \uc808\ub313\uac12\uc774 3\ubcf4\ub2e4 \ud070 \ud45c\uc900\ud654 \uc794\ucc28\ub97c \uc774\uc0c1\uac12\uc73c\ub85c \uac04\uc8fc\ud558\ub294 \uacbd\uc6b0\uac00 \ub9ce\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 #fit ordinary least squares regression model<\/span>\nols <- lm(y~x1+x2, data=df)\n\n#create plot of y-values vs. standardized residuals\n<\/span>plot(df$y, rstandard(ols), ylab=' Standardized Residuals<\/span> ', xlab=' y<\/span> ') \nabline(h= 0<\/span> )<\/strong> <\/pre>\n
\"\"<\/p>\n
 \uadf8\ub798\ud504\uc5d0\uc11c \uc57d 3\uc758 \ud45c\uc900\ud654\ub41c \uc794\ucc28\ub97c \uac16\ub294 \ub450 \uac1c\uc758 \uad00\uce21\uce58\uac00 \uc788\uc74c\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc774\ub294 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub450 \uac00\uc9c0 \uc7a0\uc7ac\uc801 \uc774\uc0c1\uac12\uc774 \uc788\uc74c\uc744 \uc758\ubbf8\ud558\ubbc0\ub85c \ub300\uc2e0 \uac15\ub825\ud55c \ud68c\uadc0 \ubd84\uc11d\uc744 \ud1b5\ud574 \uc774\uc810\uc744 \uc5bb\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 3\ub2e8\uacc4: \uac15\ub825\ud55c \ud68c\uadc0 \uc218\ud589<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c\uc73c\ub85c rlm()<\/strong> \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec \uac15\ub825\ud55c \ud68c\uadc0 \ubaa8\ub378\uc744 \ub9de\ucdb0\ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 library<\/span> (MASS)<\/span>\n\n#fit robust regression model<\/span>\nrobust <- rlm(y~x1+x2, data=df)<\/strong><\/pre>\n
 \uc774 \uac15\ub825\ud55c \ud68c\uadc0 \ubaa8\ub378\uc774 OLS \ubaa8\ub378\uacfc \ube44\uad50\ud558\uc5ec \ub370\uc774\ud130\uc5d0 \ub354 \uc798 \ub9de\ub294\uc9c0 \uc5ec\ubd80\ub97c \ud655\uc778\ud558\uae30 \uc704\ud574 \uac01 \ubaa8\ub378\uc758 \uc794\ucc28 \ud45c\uc900 \uc624\ucc28\ub97c \uacc4\uc0b0\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \uc794\ucc28 \ud45c\uc900 \uc624\ucc28(RSE)\ub294 \ud68c\uadc0 \ubaa8\ub378\uc5d0\uc11c \uc794\ucc28\uc758 \ud45c\uc900 \ud3b8\ucc28\ub97c \uce21\uc815\ud558\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. CSR \uac12\uc774 \ub0ae\uc744\uc218\ub85d \ubaa8\ub378\uc774 \ub370\uc774\ud130\uc5d0 \ub354 \uc798 \uc801\ud569\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ub2e4\uc74c \ucf54\ub4dc\ub294 \uac01 \ubaa8\ub378\uc758 RSE\ub97c \uacc4\uc0b0\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4.<\/span><\/p>\n
 #find residual standard error of ols model\n<\/span>summary(ols)$sigma\n\n[1] 49.41848\n\n#find residual standard error of ols model\n<\/span>summary(robust)$sigma\n\n[1] 9.369349\n<\/strong><\/pre>\n
 \ub85c\ubc84\uc2a4\ud2b8 \ud68c\uadc0 \ubaa8\ub378\uc758 RSE\uac00 \uc77c\ubc18 \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0 \ubaa8\ub378\uc758 RSE\ubcf4\ub2e4 \ud6e8\uc52c \ub0ae\ub2e4\ub294 \uac83\uc744 \uc54c \uc218 \uc788\uc2b5\ub2c8\ub2e4. \uc774\ub294 \ub85c\ubc84\uc2a4\ud2b8 \ud68c\uadc0 \ubaa8\ub378\uc774 \ub370\uc774\ud130\uc5d0 \ub354 \uc798 \ub9de\ub294\ub2e4\ub294 \uac83\uc744 \uc758\ubbf8\ud569\ub2c8\ub2e4.<\/span><\/p>\n
 \ucd94\uac00 \ub9ac\uc18c\uc2a4<\/strong><\/span><\/h3>\n
 R\uc5d0\uc11c \ub2e8\uc21c \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \ub2e4\uc911 \uc120\ud615 \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a>
 R\uc5d0\uc11c \ub2e4\ud56d\uc2dd \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"
\uac15\ub825\ud55c \ud68c\uadc0\ub294 \uc791\uc5c5 \uc911\uc778 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \uc774\uc0c1\uce58\ub098 \uc601\ud5a5\ub825 \uc788\ub294 \uad00\uce21\uce58\uac00 \uc788\uc744 \ub54c \uc77c\ubc18 \ucd5c\uc18c \uc81c\uacf1 \ud68c\uadc0\uc758 \ub300\uc548\uc73c\ub85c \uc0ac\uc6a9\ud560 \uc218 \uc788\ub294 \ubc29\ubc95\uc785\ub2c8\ub2e4. R\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub824\uba74 \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\ub294 MASS \ud328\ud0a4\uc9c0\uc758 rlm() \ud568\uc218\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4. \ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\ub294 \uc8fc\uc5b4\uc9c4 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud574 R\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95\uc744 \ubcf4\uc5ec\uc90d\ub2c8\ub2e4. 1\ub2e8\uacc4: \ub370\uc774\ud130 \uc0dd\uc131 \uba3c\uc800 \uc791\uc5c5\ud560 \uac00\uc9dc \ub370\uc774\ud130\uc138\ud2b8\ub97c […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[20],"tags":[],"class_list":["post-1606","post","type-post","status-publish","format-standard","hentry","category-20"],"yoast_head":"\nR\uc5d0\uc11c \uac15\ub825\ud55c \ud68c\uadc0\ub97c 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