PERBANDINGAN METODE KUADRAT TERKECIL DAN METODE BAYES DALAM MENGESTIMASI MODEL REGRESI LINIER SEDERHANA DENGAN GALAT HETEROSKEDASTISITAS

Authors

  • RYAN HANDANI
  • MAIYASTRI MAIYASTRI
  • RITA DIANA

DOI:

https://doi.org/10.25077/jmu.6.3.47-54.2017

Abstract

Analisis regresi merupakan salah satu metode dalam statistik yang digunakan untuk melihat hubungan antara variabel bebas dengan variabel tak bebas, salah satunya yang dinyatakan dalam model regresi linier sederhana, dimana dalam pendugaan parameternya terdapat dua pendekatan yaitu, pendekatan klasik pendekatan Bayesian. Salah satu metode estimasi dengan pendekatan klasik adalah Metode Kuadrat Terkecil (MKT), dimana dalam MKT terdapat asumsi-asumsi yang harus dipenuhi diantaranya adalah error berdistribusi normal, independent dan identik (homogen). Jika salah satu asumsi dilanggar seperti errornya tidak identik (heteros) maka metode Bayes dapat digunakan untuk mengatasi masalah tersebut. Dengan metode Bayes diperoleh hasil bias yang lebih kecil dibandingkan dengan MKT.

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Published

03-11-2017

Issue

Vol. 6 No. 3 (2017)

Section

Articles

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