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Article
Multidisciplinary Sciences
Naif Alotaibi et al.
Summary: In this article, a new extension of the Kumaraswamy (Ku) model called the Kavya Manoharan Kumaraswamy (KMKu) model is introduced. The KMKu model exhibits similar shape forms of the probability density function as the Ku model for different parameter values, including bathtub, unimodal, increasing, and decreasing shapes. The response function of the KMKu model can also take on bathtub, U-shaped, J-shaped, and increasing forms. Various statistical and computational properties, as well as four measures of entropy, were examined. The maximum likelihood approach was used to estimate the parameters of the KMKu model using simple and ranked set sampling. A simulation experiment demonstrated the efficiency of ranked set sampling compared to simple random sampling. The flexibility of the KMKu model was verified through analysis of three real-world datasets.
Article
Mathematics
Usman Shahzad et al.
Summary: Using auxiliary information, this paper proposes two families of estimators based on an adaptation of the estimators presented by recent researchers, and introduces a new family of calibration estimators under stratified median ranked set sampling (MRSS). The performance of the adapted and proposed estimators is evaluated through a simulation study using real and artificial datasets. Real-world data on the body mass index (BMI) of 800 people in Turkey in 2014 is used as a research variable, with age as an auxiliary variable.
Article
Mathematics, Applied
Shashi Bhushan et al.
Summary: This paper presents efficient difference- and ratio-type imputation methods under ranked set sampling with missing values. The proposed methods outperform existing ones according to theoretical and computational analyses on various populations. Skewness and kurtosis are also taken into consideration for evaluating the efficiency of the suggested imputation methods.
Article
Mathematics, Applied
Shashi Bhushan et al.
Summary: Ranked set sampling (RSS) has been proven to be an efficient alternative to simple random sampling (SRS), and the use of auxiliary information improves estimation procedures' efficiency. This study proposes optimal classes of estimators under RSS by using multi-auxiliary information to achieve higher efficiency and discuss optimality issues. It is found that the proffered estimators include the ordinary mean estimator, traditional regression, and ratio estimators. The study reports expressions of bias and mean square error and demonstrates the superiority of the proffered estimators over reviewed works under certain optimality conditions. Computational study using artificial and natural populations supports the theoretical results, showing that the proffered estimators outperform conventional estimators. Appropriate advice is also suggested for survey persons.
Article
Multidisciplinary Sciences
Abdullah Mohammed Alomair et al.
Summary: This paper proposes a generalized class of minimum covariance-determinant (MCD)-based calibration estimators and presents a novel class of MCD-based calibrated estimators under a stratified median-ranked-set-sampling (MRSS) design. Real and artificial datasets are utilized to assess and compare the performance of the estimators. The results show that the proposed estimators have minimum and maximum PREs in different scenarios.
Article
Mathematics, Interdisciplinary Applications
Fathy H. Riad et al.
Summary: The paper proposes a likelihood function based on the extended neoteric ranked set sampling (ENRSS) plan for estimating the parameters of the inverted Nadarajah-Haghighi distribution. A Monte Carlo simulation study is conducted to evaluate its performance, and the efficiency of the estimated parameters is compared with other ranked set sampling methods. The results are satisfactory and consistent with the previous findings by Taconeli and Cabral in 2019.
Article
Computer Science, Software Engineering
Shashi Bhushan et al.
Summary: This article proposes a new efficient logarithmic class of estimators for estimating the population mean using ranked set sampling with multi-auxiliary information. The bias and mean square error of the proposed estimators are reported up to the first order of approximation. Analytical and numerical analyses demonstrate that the proposed estimators are always better than their competitors. Empirical and simulation studies further support these findings.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Mathematics
Shashi Bhushan et al.
Summary: This paper considers efficient combined and separate classes of estimators for population mean estimation in stratified ranked set sampling with bivariate auxiliary information. The mean square error expressions of the proposed estimators are derived and conditions for their superiority over existing estimators are obtained. Numerical and simulation studies with real and artificially generated populations support the superiority of the proposed estimators.
JOURNAL OF MATHEMATICS
(2022)
Article
Engineering, Multidisciplinary
Hassan M. Aljohani et al.
Summary: This paper focuses on estimating the parameters of the modified Kies exponential distribution using classical estimation methods and ranked set sampling, finding that likelihood estimation can obtain maximum likelihood estimators. A Monte Carlo simulation was used to compare efficiencies of different designs, with the relative efficiency of RSS design increasing with the number of cycles for the MKEx distribution.
ALEXANDRIA ENGINEERING JOURNAL
(2021)
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Statistics & Probability
Ramkrishna S. Solanki et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2016)
Article
Statistics & Probability
Daniel F. Linder et al.
JOURNAL OF APPLIED STATISTICS
(2015)
Article
Statistics & Probability
Ramkrishna S. Solanki et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2014)
Article
Computer Science, Interdisciplinary Applications
Housila P. Singh et al.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2014)
Article
Statistics & Probability
Housila P. Singh et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2013)
Article
Statistics & Probability
Javid Shabbir et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2011)
Article
Statistics & Probability
Nursel Koyuncu et al.
JOURNAL OF APPLIED STATISTICS
(2010)
Article
Statistics & Probability
Housila Singh et al.
METRON-INTERNATIONAL JOURNAL OF STATISTICS
(2010)
Article
Statistics & Probability
Nursel Koyuncu et al.
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
(2009)
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Statistics & Probability
Cem Kadilar et al.
STATISTICAL PAPERS
(2009)
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Statistics & Probability
Housila P. Singh et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2008)
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Statistics & Probability
Javid Shabbir et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2006)
Article
Statistics & Probability
C Kadilar et al.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2005)
