Efosa Edionwe - Academia.edu (original) (raw)

Efosa Edionwe

Uploads

Papers by Efosa Edionwe

Research paper thumbnail of Local Linear Regression and the problem of dimensionality: a remedial strategy via a new locally adaptive bandwidths selector

Journal of Applied Statistics, 2022

Research paper thumbnail of Local Bandwidths for Improving Performance Statistics of Model-Robust Regression 2

Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines pa... more Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.

Research paper thumbnail of A New Function for Generating Local Bandwidths for Semi-Parametric MRR2 Model in Response Surface Methodology

The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodness-of-fit statistics.

Research paper thumbnail of An Improved Robust Regression Model for Response Surface Methodology

Croatian Operational Research Review

Research paper thumbnail of Local Linear Regression and the problem of dimensionality: a remedial strategy via a new locally adaptive bandwidths selector

Journal of Applied Statistics, 2022

Research paper thumbnail of Local Bandwidths for Improving Performance Statistics of Model-Robust Regression 2

Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines pa... more Model-Robust Regression 2 (MRR2) method is a semi-parametric regression approach that combines parametric and nonparametric fits. The bandwidth controls the smoothness of the nonparametric portion. We present a methodology for deriving data-driven local bandwidth that enhances the performance of MRR2 method for fitting curves to data generated from designed experiments.

Research paper thumbnail of A New Function for Generating Local Bandwidths for Semi-Parametric MRR2 Model in Response Surface Methodology

The modeling phase of response surface methodology (RSM) involves the application of regression t... more The modeling phase of response surface methodology (RSM) involves the application of regression techniques to fitting a curve to the data generated from a designed experiment. The model-robust regression 2 (MRR2) method is a semi-parametric regression approach that combines portions of estimates from both the parametric and the nonparametric regression approaches via a mixing parameter. However, the robustness of the estimates from the MRR2 approach depends largely on the choice of bandwidth. Utilizing the cross-validation approach to bandwidth selection, we propose a methodology for deriving a data-driven function that generates local bandwidths for the MRR2 approach. Using two examples from the literature and a simulation study, we show that, in comparison with other regression methods, the results obtained from the MRR2 approach utilizing the proposed function offer remarkable improvements in the goodness-of-fit statistics.

Research paper thumbnail of An Improved Robust Regression Model for Response Surface Methodology

Croatian Operational Research Review

Log In