खोज परिणाम - Kayode Ayinde
-
1
A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model
प्रकाशित 2022-12-01पूर्ण पाठ प्राप्त करेंDespite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated. This study proposes an alternative estimator to the OLS and other existing ridge-type estimator...
लेख -
2
M Robust Weighted Ridge Estimator in Linear Regression Model
प्रकाशित 2023-08-01पूर्ण पाठ प्राप्त करेंCorrelated regressors are a major threat to the performance of the conventional ordinary least squares (OLS) estimator. The ridge estimator provides more stable estimates in this circumstance. However, both OLS and Ridge estimators are sensitive to outlying observations. In previous studies, the rob...
लेख -
3
On the biased Two-Parameter Estimator to Combat Multicollinearity in Linear Regression Model
प्रकाशित 2022-12-01पूर्ण पाठ प्राप्त करेंThe most popularly used estimator to estimate the regression parameters in the linear regression model is the ordinary least-squares (OLS). The existence of multicollinearity in the model renders OLS inefficient. To overcome the multicollinearity problem, a new two-parameter estimator, a biased two...
लेख -
4
Robust weighted ridge regression based on S – estimator
प्रकाशित 2023-12-01पूर्ण पाठ प्राप्त करेंOrdinary least squares (OLS) estimator performance is seriously threatened by correlated regressors often called multicollinearity. Multicollinearity is a situation when there is strong relationship between any two exogenous variables. In this case, the ridge estimator offers more reliable estimatio...
लेख