Statistical inference for the Nadarajah-Haghighi distribution based on ranked set sampling with applications

In this article, the maximum likelihood and Bayes inference methods are discussed for determining the two unknown parameters and specific lifetime parameters of the Nadarajah-Haghighi distribution, such as the survival and hazard rate functions, with the inclusion of ranked set sampling and simple random sampling. The estimated confidence intervals for the two parameters and any function of them are developed based on the Fisher-information matrix. Metropolis-Hastings algorithm and Lindley-approximation are used for generating the Bayes estimates and related highest posterior density credible ranges for the unknown parameters and reliability parameters under the presumption of conjugate gamma priors. A Monte-Carlo simulation study and a real-life data set have been used to assess the efficacy of the proposed methods

Bayesian Estimation and Prediction for Pareto Distribution based on Ranked set Sampling

In this paper, we provide Bayesian estimation for the parameters of the Pareto distribution based on simple random sample (SRS) and ranked set sampling (RSS) in two cases, one cycle and m-cycle. Posterior risk of the derived estimators are also obtained by using squared error loss (SEL). Two-sample Bayesian prediction for future observations are obtained by using SRS and RSS in two cases, one cycle and m-cycle. A simulation data for SRS and RSS for one cycle and two cycle are used to illustrate the results

1950 summary of results of fungicide tests on fruit and nut trees /

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