ANALISIS ESTIMASI PARAMETER REGRESI KUANTIL DENGAN METODE BOOTSTRAP

Authors

  • Mesi Oktafia
  • Ferra Yanuar
  • Maiyastri .

DOI:

https://doi.org/10.25077/jmu.5.1.125-130.2016

Abstract

Abstrak. Regresi kuantil merupakan salah satu metode regresi dengan pendekatan
memisahkan atau membagi data menjadi kuantil-kuantil tertentu. Metode pendekatan
yang dilakukan adalah dengan meminimumkan error mutlak berbobot yang tidak
simetris dan menduga fungsi kuantil bersyarat pada suatu sebaran data. Pendugaan parameter
regresi kuantil ini tidak membutuhkan asumsi parametertik. Parameter model
yang dihasilkan kemudian diuji keakuratannya dengan menggunakan metode Bootstrap.
Metode Bootstrap merupakan suatu teknik pendekatan nonparametrik untuk menaksir
berbagai kuantitas statistik seperti mean, standar error, dan bias suatu estimasi atau
untuk membentuk interval kondensi dengan mengikuti algoritma tertentu. Pada kajian
ini estimasi parameter regresi kuantil dengan metode Bootstrap diperoleh bahwa hasil
estimasi parameter regresi kuantil sudah cukup akurat, karena nilai estimasi parameter
regresi kuantil dengan metode Bootstrap hampir mendekati nilai estimasi regresi kuantil
untuk data simulasi. Selanjutnya estimasi parameter regresi kuantil dengan metode Bootstrap
diperoleh nilai mean square error (MSE) yang cukup kecil untuk setiap estimasi
parameter pada setiap kuantilnya, ini mengindikasikan bahwa nilai estimasi parameter
regresi kuantil dengan metode Bootstrap sudah cukup baik.

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Published

01-03-2016

How to Cite

Oktafia, M., Yanuar, F., & ., M. (2016). ANALISIS ESTIMASI PARAMETER REGRESI KUANTIL DENGAN METODE BOOTSTRAP. Jurnal Matematika UNAND, 5(1), 125–130. https://doi.org/10.25077/jmu.5.1.125-130.2016

Issue

Vol. 5 No. 1 (2016)

Section

Articles

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