In this article, we use ranked set sampling (RSS) to develop a Bayesian analysis based on record statistics values. Maximum likelihood estimation (MLE) and Bayes estimators are derived for linear exponential distribution from a simple random sample (SRS) and record ranked set sampling (RRSS) (one- and m-cycle). These estimators are compared via their biases and mean squared error (MSE). This is done with respect to both symmetric and asymmetric loss function. Two numerical examples are used to illustrate these results.
Digital Object Identifier (DOI)
M. Mohie El-Din, Mostafa; S. Kotb, Mohamed; and A. Newer, Haidy
"Inference for Linear Exponential Distribution Based on Record Ranked Set Sampling,"
Journal of Statistics Applications & Probability: Vol. 10
, Article 19.
Available at: https://dc.naturalspublishing.com/jsap/vol10/iss2/19