Bu test tipik olarak ekonometri alan\u0131nda zaman serisi verileriyle belirli bir zamanda verilerde yap\u0131sal bir k\u0131r\u0131lma olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in kullan\u0131l\u0131r.<\/span><\/p>\n A\u015fa\u011f\u0131daki ad\u0131m ad\u0131m \u00f6rnek, Python’da bir Chow testinin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fini g\u00f6sterir.<\/span><\/p>\n \u0130lk \u00f6nce sahte veriler olu\u015fturaca\u011f\u0131z:<\/span><\/p>\n Daha sonra verileri g\u00f6rselle\u015ftirmek i\u00e7in basit bir da\u011f\u0131l\u0131m grafi\u011fi olu\u015fturaca\u011f\u0131z:<\/span> <\/p>\n Da\u011f\u0131l\u0131m grafi\u011finden verilerdeki e\u011filimin x = 10’da de\u011fi\u015fti\u011fini g\u00f6rebiliriz.<\/span><\/p>\n B\u00f6ylece x = 10 noktas\u0131nda verilerde yap\u0131sal bir k\u0131r\u0131lma noktas\u0131n\u0131n olup olmad\u0131\u011f\u0131n\u0131 tespit etmek i\u00e7in Chow testini ger\u00e7ekle\u015ftirebiliriz.<\/span><\/p>\n Chow testi ger\u00e7ekle\u015ftirmek i\u00e7in Python’daki chowtest<\/a> paketinin chowtest fonksiyonunu kullanabiliriz.<\/span><\/span><\/p>\n \u00d6ncelikle bu paketi pip kullanarak kurmam\u0131z gerekiyor:<\/span><\/p>\n Daha sonra Chow testini ger\u00e7ekle\u015ftirmek i\u00e7in a\u015fa\u011f\u0131daki s\u00f6zdizimini kullanabiliriz:<\/p>\n Chowtest()<\/strong> i\u015flevindeki ba\u011f\u0131ms\u0131z de\u011fi\u015fkenlerin anlam\u0131 \u015fu \u015fekildedir:<\/span><\/p>\n Test sonucundan \u015funlar\u0131 g\u00f6rebiliriz:<\/span><\/p>\n P de\u011feri 0,05’ten k\u00fc\u00e7\u00fck oldu\u011fundan testin s\u0131f\u0131r hipotezini reddedebiliriz. Bu, verilerde yap\u0131sal bir k\u0131r\u0131lma noktas\u0131n\u0131n mevcut oldu\u011funu s\u00f6ylemek i\u00e7in yeterli kan\u0131t\u0131m\u0131z oldu\u011fu anlam\u0131na gelir.<\/span><\/p>\n Ba\u015fka bir deyi\u015fle, iki regresyon \u00e7izgisi, modeli verilere tek bir regresyon \u00e7izgisine g\u00f6re daha etkili bir \u015fekilde s\u0131\u011fd\u0131rabilir.<\/span><\/p>\n A\u015fa\u011f\u0131daki e\u011fitimlerde Python’da di\u011fer yayg\u0131n testlerin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fi a\u00e7\u0131klanmaktad\u0131r:<\/span><\/p>\n Python’da Granger Nedensellik Testi Nas\u0131l Yap\u0131l\u0131r?<\/a> \u0130ki farkl\u0131 regresyon modelinin farkl\u0131 veri setleri \u00fczerindeki katsay\u0131lar\u0131n\u0131n e\u015fit olup olmad\u0131\u011f\u0131n\u0131 test etmek i\u00e7in Chow testi kullan\u0131l\u0131r. Bu test tipik olarak ekonometri alan\u0131nda zaman serisi verileriyle belirli bir zamanda verilerde yap\u0131sal bir k\u0131r\u0131lma olup olmad\u0131\u011f\u0131n\u0131 belirlemek i\u00e7in kullan\u0131l\u0131r. A\u015fa\u011f\u0131daki ad\u0131m ad\u0131m \u00f6rnek, Python’da bir Chow testinin nas\u0131l ger\u00e7ekle\u015ftirilece\u011fini g\u00f6sterir. 1. Ad\u0131m: Verileri olu\u015fturun \u0130lk […]<\/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-2473","post","type-post","status-publish","format-standard","hentry","category-rehber"],"yoast_head":"\n 1. Ad\u0131m: Verileri olu\u015fturun<\/strong><\/span><\/h3>\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. Ad\u0131m: Verileri g\u00f6rselle\u015ftirin<\/strong><\/span><\/h3>\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![\"\"](\"https:\/\/statorials.org\/wp-content\/uploads\/2023\/08\/chow11.png\")
<\/p>\n Ad\u0131m 3: Chow Testini Ger\u00e7ekle\u015ftirin<\/strong><\/span><\/h3>\n
pip install<\/span> chowtest\n<\/strong><\/pre>\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\n
\n
Ek kaynaklar<\/strong><\/span><\/h3>\n
Python’da Breusch-Pagan testi nas\u0131l yap\u0131l\u0131r<\/a>
Python’da White Testi Nas\u0131l Ger\u00e7ekle\u015ftirilir<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"