Our proposed shrinkage regression-based methods can provide accurate missing value estimation, they are competitive alternatives to the existing regression- ...

Dec 13, 2013 · Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the ...

This work proposes shrinkage regression-based methods, which incorporate the least squares principle, utilize a shrinkage estimation approach to adjust the ...

Dec 13, 2013 · Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the ...

Missing values commonly occur in the microarray data, which usually contain more than 5% missing values with up to 90% of genes affected.

In this study, we propose using the well-known shrinkage estimation approach to improve three existing regression- based methods (LLSimpute [18], SLLSimpute [19] ...

Besides, we investigate different similarity filtering metrics to select neighbor genes and develop another four imputation methods under the framework.

Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression ...

Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression ...

Simulation results show that the proposed methods provide more accurate missing value estimation in six testing microarray datasets than the existing regression ...