Essential oils retention indices prediction using a robust screening approach and a sparse QSRR

What is it about?

New robust QSRR model is proposed to be an efficient tool to predict retention indices of essential oils components.

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Why is it important?

The modeling method is new in the prediction of the retention indices of essential oils. In addition, the proposed method was developed to be efficient based on the following steps: First, dimension reduction was performed using the proposed modified robust sure independence screening (MR-SIS) method. Second, prediction of RIs was made using the proposed robust sparse QSRR with smoothly clipped absolute deviation (SCAD) penalty.

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