Extropy information of maximum and minimum ranked set sampling with unequal samples

Qiu, Guoxin; Eftekharian, Abbas

doi:10.1080/03610926.2019.1678640

Cited by 30 publications

(9 citation statements)

References 22 publications

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“…Raqab and Qiu [14] investigated the properties of extropy on RSS data and suggested a discrimination information concept based on extropy as a discrimination tool between different data sets. Qiu and Eftekharian [12] developed some properties of extropy using stochastic orders on maximum and minimum RSS with unequal samples. In the present paper, we study the notions of the information content of SRSS data set under extropy information measure and monotonic properties using stochastic orders.…”

Section: Introductionmentioning

confidence: 99%

On Extropy Properties and Discrimination Information of Different Stratified Sampling Schemes

Eftekharian¹,

Qiu

2021

Prob. Eng. Inf. Sci.

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Ranked set sampling (RSS) and some of its variants are sampling designs that are applied widely in different areas. When the underlying population contains different subpopulations, we can use stratified ranked set sampling (SRSS) which combines the advantages of stratification with RSS. In the present paper, we consider the information content of SRSS in terms of extropy measure. Some results using stochastic orders properties are obtained. The effect of imperfect ranking on discrimination information is analytically investigated. It is proved that discrimination information between the perfect SRSS and simple random sampling (SRS) data sets performs better than that of between the imperfect SRSS and SRS data sets.

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Section: Introductionmentioning

confidence: 99%

On Extropy Properties and Discrimination Information of Different Stratified Sampling Schemes

Eftekharian¹,

Qiu

2021

Prob. Eng. Inf. Sci.

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“…Later estimation of parameters of various commonly used distributions has been carried out using RSS. For more details, see Chen et al [2][3][4][5][6], Qiu and Eftekharian [11] and Stokes [17]. However, ranking accuracy affects the efficiency of the estimator.…”

Section: Introductionmentioning

confidence: 99%

Ratio Estimation of the Population Mean Using Auxiliary Information Under the Optimal Sampling Design

Long¹,

Chen²,

Yang³

et al. 2020

Prob. Eng. Inf. Sci.

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Cost-effective sampling design is a problem of major concern in some experiments especially when the measurement of the characteristic of interest is costly or painful or time-consuming. In this article, we investigate ratio-type estimators of the population mean of the study variable, involving either the first or the third quartile of the auxiliary variable, using ranked set sampling (RSS) and extreme ranked set sampling (ERSS) schemes. The properties of the estimators are obtained. The estimators in RSS and ERSS are compared to their counterparts in simple random sampling (SRS) for normal data. The numerical results show that the estimators in RSS and ERSS are significantly more efficient than their counterparts in SRS.

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“…There are many available studies that have developed and generalized the method of sampling used in RSS scheme and they efficiently estimate the population parameter comparing to the SRS scheme. Recently, Qiu & Eftekharian (2020) studied information content of minimum ranked set sampling procedure with unequal samples (MinRSSU) as useful modification of RSS procedure in terms of extropy. In the MinRSSU, we draw m simple random samples, where the size of the ith samples is i, i = 1, ..., m. The one-cycle MinRSSU involves an initial ranking of m samples of size m as follows:…”

Section: Introductionmentioning

confidence: 99%

“…Eskandarzadeh et al (2018) considered information measures of maximum ranked set sampling procedure with unequal samples in terms of Shannon entropy, Rényi entropy and Kullback-Leibler information, instead Tahmasebi et al (2020) in terms of Tsallis entropy. More recently, Qiu & Eftekharian (2020) studied information content of MinRSSU in terms of extropy and Raqab & Qiu (2019) considered the problems of uncertainty and information content of RSS data based on extropy measure and the related monotonic properties and stochastic comparisons.…”

Section: Introductionmentioning

confidence: 99%

“…Qiu (2017) explored some characterization results, monotone properties, and lower bounds of extropy of order statistics and record values. Also, Qiu & Eftekharian (2020) and Raqab & Qiu (2019) considered the information measure of extropy J(X) based on MinRSSU and RSS schemes, respectively and compared the results with their counterpart under SRS design.…”

Section: Introductionmentioning

confidence: 99%

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Cumulative Residual Extropy of Minimum Ranked Set Sampling with Unequal Samples

Kazemia¹,

Tahmasebib²,

Calì³

et al. 2020

Preprint

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Recently, an alternative measure of uncertainty called cumulative residual extropy (CREX) was proposed by Jahanshahi et al. (2019). In this paper, we consider uncertainty measures of minimum ranked set sampling procedure with unequal samples (MinRSSU) in terms of CREX and its dynamic version and we compare the uncertainty and information content of CREX based on MinRSSU and simple random sampling (SRS) designs. Also, using simulation, we study on new estimators of CREX for MinRSSU and SRS designs in terms of bias and mean square error. Finally, we provide a new discrimination measure of disparity between the distribution of MinRSSU and parental data SRS.

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Extropy information of maximum and minimum ranked set sampling with unequal samples

Cited by 30 publications

References 22 publications

On Extropy Properties and Discrimination Information of Different Stratified Sampling Schemes

On Extropy Properties and Discrimination Information of Different Stratified Sampling Schemes

Ratio Estimation of the Population Mean Using Auxiliary Information Under the Optimal Sampling Design

Cumulative Residual Extropy of Minimum Ranked Set Sampling with Unequal Samples

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