Uji Park Dan Uji Breusch Pagan Godfrey Dalam Pendeteksian Heteroskedastisitas Pada Analisis Regresi

  • Siska Andriani UIN Raden Intan Lampung
Keywords: analysis, Breusch, regression, heteroscedasticity

Abstract

Homoskedastisitas is one of the conditions are fulfilled classical assumptions in the regression analysis, if not met this means homoskedastisitas error variance is not constant and is said to occur heteroscedasticity problem. Test Park and Pagan Godfrey Breusch test is a statistical test to detect whether there is a problem of heteroscedasticity in the regression equation. The problem is how to test the results of detection heteroskedastisitas Park and Breusch Pagan Godfrey test, which is more effective test.Based on the results of research and discussion can be concluded that the detection of the three cases of data acquired two pieces of data in the test with both test detected heteroskedasticity problems, while one case is detected by the test Breusch heteroskedastisitas Pagan Godfrey Park but the test was not detected. Values mean square error (MSE) test Breusch Pagan Godfrey smaller than the test Park so it can be said Pagan Godfrey Breusch method used more effectively. Thus, in detecting problems hetereoskedastisitas should use Breusch Pagan Godfrey test because they have better accuracy than tests Park.

References

Birkes, D. d. (2011). Nonparametric Regression. Sohravardi: Persian Philosopher , 1155-1191.

Davino, C. M. (2014). Quantile Regression: Understanding How and Why. Review of Economics and Statistics , 22-62.

Farizal, A. R. (2014). Model Peramalan Konsumsi Bahan Bakar Jenis Premium Di Indonesia Dengan Regresi Linier Berganda. Jurnal Ilmiah Teknik Industri , 13 (2), 1412-6869.

Ghozali, Imam. (2009). Ekonometrika Teori, Konsep, dan Aplikasi dengan SPSS 17. Semarang: Badan Penerbit Universitas Diponegoro.

Hajarisman, N. (2012). Penaksiran Parameter Model Regresi Beta untuk Memodelkan Data Proporsi. Statistika , 12 (1), 9-18.

Hollander, M. D. (2015). Regression Problems. Review of Economics and Statistics , 451-494.

Ivan, K. C. (2016). Analisis Model Regresi Nonparametrik Sirkular Linear Berganda. E-Jurnal Matematika , 5 (2), 52-58.

Muliawan, A. D. (2015). A Review On The Use Of Regression Analysis In Studies Of Audit Quality. Jurnal Tata Kelola & Akuntabilitas Keuangan Negara , 1 (1), 107-127.

Nurlaila, Z. M. (2017). Penerapan Metode Newey West Dalam Mengoreksi Standard Error Ketika Terjadi Heteroskedastisitas dan Autokorelasi Pada Aisnalis Regresi. E-Jurnal Matematika , 6 (1), 7-14.

Pradawati, P. S. (2013). Penerapan Regresi Binomial Negatif Untukl Mengatasi Overdispersi Pada Regresi Poisson. E-Jurnal Matematika , 2 (2), 6-10.

Ratnasari, N. P. (2014). Aplikasi Regresi Data Panel Dengan Pendekatan Fixed Effect Model (Studi Kasus: PT PLN Gianyar)v. E-Jurnal Matematika , 3 (1), 1-7.

Sunarto. (2015). Pengaruh Kualitas Produk Terhadap Keputusan Pembelian Pada Toko Kerjinan Kulit Kartika Magetan. Equilibrium , 3 (2), 191-205.

Tayeb, T. (2012). Efektivitas Metode New Stepwise Dalam Pemilihan Variabel Pada Model Regresi Ganda. Lentera Pendidikan , 15 (2), 161-174.

Uthami, I. A. (2013). Regresi Kuantil Median Untuk Mengatasi Heteroskedastisitas Pada Analisis Regresi. e-Jurnal Matematika , 2 (1), 6-13.

Published
2017-06-19