Kernel-based entropy estimation in ranked set sampling

This paper is concerned with kernel-based estimation of the entropy in ranked set sampling. Theoretical properties of the proposed estimator are studied and com- pared with those of the rival estimator in simple random sampling. An application to the mutual information estimation is provided.