Estimation of the Mean of the Exponential Distribution Using Maximum Ranked Set Sampling with Unequal Samples

Biradar, B. S.; Santosha, C. D.

doi:10.4236/ojs.2014.48060

Cited by 28 publications

(10 citation statements)

References 12 publications

(17 reference statements)

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“…Recently, the authors in Ref. [21] proposed a new sampling design known as the maximum ranked set sampling procedure with unequal samples (MRSSU).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Inference for the Parameters of Kumaraswamy Distribution via Ranked Set Sampling

Jiang

Gui

2021

Symmetry

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In this paper, we address the estimation of the parameters for a two-parameter Kumaraswamy distribution by using the maximum likelihood and Bayesian methods based on simple random sampling, ranked set sampling, and maximum ranked set sampling with unequal samples. The Bayes loss functions used are symmetric and asymmetric. The Metropolis-Hastings-within-Gibbs algorithm was employed to calculate the Bayes point estimates and credible intervals. We illustrate a simulation experiment to compare the implications of the proposed point estimators in sense of bias, estimated risk, and relative efficiency as well as evaluate the interval estimators in terms of average confidence interval length and coverage percentage. Finally, a real-life example and remarks are presented.

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“…Recently, the authors in Ref. [21] proposed a new sampling design known as the maximum ranked set sampling procedure with unequal samples (MRSSU).…”

Section: Introductionmentioning

confidence: 99%

Bayesian Inference for the Parameters of Kumaraswamy Distribution via Ranked Set Sampling

Jiang

Gui

2021

Symmetry

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“…where B(i, n − i + 1) is the beta function with parameters i and n − i + 1. Biradar and Santosha (2014) proposed MRSSU to estimate the mean of the exponential distribution and indicated that MRSSU is better than that of the estimator based on SRS.…”

Section: Introductionmentioning

confidence: 99%

Cumulative Tsallis entropy for maximum ranked set sampling with unequal samples

Tahmasebi

Longobardi

Kazemi

et al. 2020

Physica A: Statistical Mechanics and its Applications

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In this paper, we consider the information content of maximum ranked set sampling procedure with unequal samples (MRSSU) in terms of Tsallis entropy which is a nonadditive generalization of Shannon entropy. We obtain several results of Tsallis entropy including bounds, monotonic properties, stochastic orders, and sharp bounds under some assumptions. We also compare the uncertainty and information content of MRSSU with its counterpart in the simple random sampling (SRS) data. Finally, we develop some characterization results in terms of cumulative Tsallis entropy and residual Tsallis entropy of MRSSU and SRS data.

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“…In this paper, we derive the Bayesian estimates of the Weibull scale parameter α based on gamma and Jeffreys prior distributions by MRSSU method proposed by Biradar and Santosha [20]. In Section 2, the preliminaries are discussed.…”

Section: Introductionmentioning

confidence: 99%

Weibull-Bayesian Estimation Based on Maximum Ranked Set Sampling with Unequal Samples

Biradar¹,

Shivanna²

2016

OJS

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A modification of ranked set sampling (RSS) called maximum ranked set sampling with unequal sample (MRSSU) is considered for the Bayesian estimation of scale parameter α of the Weibull distribution. Under this method, we use Linex loss function, conjugate and Jeffreys prior distributions to derive the Bayesian estimate of α. In order to measure the efficiency of the obtained Bayesian estimates with respect to the Bayesian estimates of simple random sampling (SRS), we compute the bias, mean squared error (MSE) and asymptotic relative efficiency of the obtained Bayesian estimates using simulation. It is shown that the proposed estimates are found to be more efficient than the corresponding one based on SRS.

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Estimation of the Mean of the Exponential Distribution Using Maximum Ranked Set Sampling with Unequal Samples

Cited by 28 publications

References 12 publications

Bayesian Inference for the Parameters of Kumaraswamy Distribution via Ranked Set Sampling

Bayesian Inference for the Parameters of Kumaraswamy Distribution via Ranked Set Sampling

Cumulative Tsallis entropy for maximum ranked set sampling with unequal samples

Weibull-Bayesian Estimation Based on Maximum Ranked Set Sampling with Unequal Samples

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