{"id":2470,"date":"2023-07-22T03:07:20","date_gmt":"2023-07-22T03:07:20","guid":{"rendered":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3\/"},"modified":"2023-07-22T03:07:20","modified_gmt":"2023-07-22T03:07:20","slug":"%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3","status":"publish","type":"post","link":"https:\/\/statorials.org\/ko\/%e1%84%91%e1%85%a1%e1%84%8b%e1%85%b5%e1%84%8a%e1%85%a5%e1%86%ab%e1%84%8b%e1%85%a6%e1%84%89%e1%85%a5-%e1%84%8e%e1%85%a1%e1%84%8b%e1%85%ae-%e1%84%90%e1%85%a6%e1%84%89%e1%85%b3%e1%84%90%e1%85%b3\/","title":{"rendered":"Python\uc5d0\uc11c chow \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\ub294 \ubc29\ubc95"},"content":{"rendered":"

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Chow \ud14c\uc2a4\ud2b8\ub294<\/a> \uc11c\ub85c \ub2e4\ub978 \ub370\uc774\ud130 \uc138\ud2b8\uc5d0 \ub300\ud55c \ub450 \uac1c\uc758 \uc11c\ub85c \ub2e4\ub978 \ud68c\uadc0 \ubaa8\ub378\uc758 \uacc4\uc218\uac00 \ub3d9\uc77c\ud55c\uc9c0 \uc5ec\ubd80\ub97c \ud14c\uc2a4\ud2b8\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n

\uc774 \ud14c\uc2a4\ud2b8\ub294 \uc77c\ubc18\uc801\uc73c\ub85c \uc2dc\uacc4\uc5f4 \ub370\uc774\ud130\ub97c \uc0ac\uc6a9\ud558\ub294 \uacc4\ub7c9\uacbd\uc81c\ud559 \ubd84\uc57c\uc5d0\uc11c \ud2b9\uc815 \uc2dc\uc810\uc5d0 \ub370\uc774\ud130\uc5d0 \uad6c\uc870\uc801 \uc911\ub2e8\uc774 \uc788\ub294\uc9c0 \ud655\uc778\ud558\ub294 \ub370 \uc0ac\uc6a9\ub429\ub2c8\ub2e4.<\/span><\/p>\n

\ub2e4\uc74c \ub2e8\uacc4\ubcc4 \uc608\uc81c\uc5d0\uc11c\ub294 Python\uc5d0\uc11c Chow \ud14c\uc2a4\ud2b8\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 \uac00\uc9dc \ub370\uc774\ud130\ub97c \ub9cc\ub4ed\ub2c8\ub2e4.<\/span><\/p>\n

 import<\/span> pandas as<\/span> pd<\/span>\n\n#createDataFrame<\/span>\ndf = pd. DataFrame<\/span> ({' x<\/span> ': [1, 1, 2, 3, 4, 4, 5, 5, 6, 7, 7, 8, 8, 9, 10, 10,\n                         11, 12, 12, 13, 14, 15, 15, 16, 17, 18, 18, 19, 20, 20],\n                   ' y<\/span> ': [3, 5, 6, 10, 13, 15, 17, 14, 20, 23, 25, 27, 30, 30, 31,\n                         33, 32, 32, 30, 32, 34, 34, 37, 35, 34, 36, 34, 37, 38, 36]})\n\n#view first five rows of DataFrame\n<\/span>df. head<\/span> ()\n\n        x y\n0 1 3\n1 1 5\n2 2 6\n3 3 10\n4 4 13<\/strong><\/pre>\n
 2\ub2e8\uacc4: \ub370\uc774\ud130 \uc2dc\uac01\ud654<\/strong><\/span><\/h3>\n
 \ub2e4\uc74c\uc73c\ub85c, \ub370\uc774\ud130\ub97c \uc2dc\uac01\ud654\ud558\uae30 \uc704\ud55c \uac04\ub2e8\ud55c \uc0b0\uc810\ub3c4\ub97c \ub9cc\ub4e4\uc5b4 \ubcf4\uaca0\uc2b5\ub2c8\ub2e4.<\/span> <\/p>\n
 import<\/span> matplotlib. pyplot<\/span> as<\/span> plt\n\n#create scatterplot\n<\/span>plt. plot<\/span> (df. x<\/span> , df. y<\/span> , ' o<\/span> ')\n<\/strong><\/span><\/pre>\n
\"\"<\/p>\n
 \uc0b0\uc810\ub3c4\uc5d0\uc11c \ub370\uc774\ud130\uc758 \ucd94\uc138\uac00 x = 10\uc5d0\uc11c \ubcc0\ud558\ub294 \uac83\uc73c\ub85c \ub098\ud0c0\ub098\ub294 \uac83\uc744 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 \ub530\ub77c\uc11c Chow \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud558\uc5ec x = 10\uc758 \ub370\uc774\ud130\uc5d0 \uad6c\uc870\uc801 \uc911\ub2e8\uc810\uc774 \uc788\ub294\uc9c0 \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n
 3\ub2e8\uacc4: \ucc28\uc6b0 \ud14c\uc2a4\ud2b8 \uc218\ud589<\/strong><\/span><\/h3>\n
 Python\uc5d0\uc11c chowtest<\/a> \ud328\ud0a4\uc9c0\uc758 chowtest \ud568\uc218\ub97c \uc0ac\uc6a9\ud558\uc5ec Chow \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/span><\/span><\/p>\n
 \uba3c\uc800 pip\ub97c \uc0ac\uc6a9\ud558\uc5ec \uc774 \ud328\ud0a4\uc9c0\ub97c \uc124\uce58\ud574\uc57c \ud569\ub2c8\ub2e4.<\/span><\/p>\n
 pip install<\/span> chowtest\n<\/strong><\/pre>\n
 \uadf8\ub7f0 \ub2e4\uc74c \ub2e4\uc74c \uad6c\ubb38\uc744 \uc0ac\uc6a9\ud558\uc5ec Chow \ud14c\uc2a4\ud2b8\ub97c \uc218\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n
 from<\/span> chow_test import<\/span> chowtest\n\nchowtest (<\/span> y=df[[' y<\/span> ']],\n         last_index_in_model_1= 15<\/span> ,\n         first_index_in_model_2= 16<\/span> ,\n         significance_level= .05<\/span> )\n\n************************************************** *********************************\nReject the null hypothesis of equality of regression coefficients in the 2 periods.\n************************************************** *********************************\nChow Statistic: 118.14097335479373 p value: 0.0\n************************************************** *********************************\n(118.14097335479373, 1.1102230246251565e-16)\n<\/strong><\/pre>\n
 chowtest()<\/strong> \ud568\uc218\uc758 \uac1c\ubcc4 \uc778\uc218\uac00 \uc758\ubbf8\ud558\ub294 \ubc14\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/span><\/p>\n