Different Forms Biasing Parameter for Generalized Ridge Regression Estimator
نویسندگان
چکیده
منابع مشابه
Generalized Ridge Regression Estimator in Semiparametric Regression Models
In the context of ridge regression, the estimation of ridge (shrinkage) parameter plays an important role in analyzing data. Many efforts have been put to develop skills and methods of computing shrinkage estimators for different full-parametric ridge regression approaches, using eigenvalues. However, the estimation of shrinkage parameter is neglected for semiparametric regression models. The m...
متن کاملEfficient Choice of Biasing Constant for Ridge Regression
This endeavor developed a mathematical programming model, which has two main objectives minimizing variance inflation factors (VIF) and maximizing coefficient of determination, to yield an efficient biasing constant for ridge regression, which is widely used for multicollinearity problem. The multiobjective structure is handled by means of goal programming. The model allowing analysts preemtive...
متن کاملWeighted Ridge MM-Estimator in Robust Ridge Regression with Multicollinearity
This study is about the development of a robust ridge regression estimator. It is based on weighted ridge MM-estimator (WRMM) and is believed to have potentials in remedying the problems of multicollinearity. The proposed method has been compared with several existing estimators, namely ordinary least squares (OLS), robust regression based on MM estimator, ridge regression (RIDGE), weighted rid...
متن کاملCook’s distance for ridge estimator in semiparametric regression
The detection of influential observations has attracted a great deal of attention in last few decades. Most of the ideas of determining influential observations are based on single-case diagnostics with ith case deleted. The Cook’s distance are most commonly used among the other single-case diagnostics and successfully applied to various statistical models. In this article, we propose Cook’s di...
متن کاملRidge Regression Estimator: Combining Unbiased and Ordinary Ridge Regression Methods of Estimation
Statistical literature has several methods for coping with multicollinearity. This paper introduces a new shrinkage estimator, called modified unbiased ridge (MUR). This estimator is obtained from unbiased ridge regression (URR) in the same way that ordinary ridge regression (ORR) is obtained from ordinary least squares (OLS). Properties of MUR are derived. Results on its matrix mean squared er...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2019
ISSN: 0975-8887
DOI: 10.5120/ijca2019918339