On estimating the distribution function and odds using ranked set sampling

The kernel estimators of the cumulative distribution function and population odds are proposed based on ranked set sampling scheme. It is shown that the kernel estimators are more efficient than the empirical ones in view of the mean squared error criterion. It is also concluded that ranked set sampling has better performance than simple random sampling, even when the rankings are not perfect.