A Robust Ridge Regression For Multicollinearity Problem In The Presence Of Outliers In The Data
The Ordinary Least Square (OLS) is a widely used method of estimation in classical regression analysis to investigate the linear relationship among the variables of interest. The OLS estimator is the Best Linear Unbiased Estimator (BLUE) when the two assumptions are fulfilled: i) independency of exp...
محفوظ في:
المؤلف الرئيسي: | Nur Aqilah Binti Ferdaos |
---|---|
التنسيق: | أطروحة |
اللغة: | en_US |
الموضوعات: | |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Development of robust procedures for partial least square regression with application to near infrared spectral data
بواسطة: Silalahi, Divo Dharma
منشور في: (2021) -
Robust estimation of a linear regression model with heteroscedastic errors /
بواسطة: Mansor, Mansor Omar
منشور في: (1996) -
A robust ridge regression estimator in the presence of outliers and multicollinearity /
بواسطة: Marina Zahari
منشور في: (2001) -
Solution To The Multicollinearity Problem In Ridge Regression Model
بواسطة: Hanan Moh. B. Duzan -
Robust diagnostics and parameter estimation methods in linear and nonlinear regression based on nu support vector regression for high dimensional data
بواسطة: Rashid, Al-Dulaimi Abdullah Mohammed
منشور في: (2022)