Logistic Kernel: A Sensitive Biomarker for Kidney Cancer by ROC Curve

Author:

Khan Javaria Ahmad1,Akbar Atif1

Affiliation:

1. Department of Statistics Bahauddin Zakariya University, Multan, PAKISTAN

Abstract

The receiver operating characteristic (ROC) curve is a well-known graphical method to describe the accuracy of a diagnostic test. In this paper, Logistic kernel is proposed with its optimal bandwidth and mean squared error. To observe the performance of our proposed kernel estimator, the comparison is made with a Gaussian kernel by using different bandwidths and ROC curve and the area under the curve (AUC) are calculated. For illustration, Kidney cancer data is used and the logistic kernel is found more pragmatic and sensitive biomarker to detect Kidney cancer. The outstanding performance of logistic kernel is also observed in simulation studies and we recommend using nonparametric ROC curve using logistic kernel.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

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