On estimating the distribution function and odds using ranked set sampling

Eftekharian, Abbas; Razmkhah, Mostafa

doi:10.1016/j.spl.2016.10.021

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…By substituting ( 13) and ( 14) in (12), this advocates the consistency of 𝐹 ̂ * (𝑡) which completes the proof.…”

Section: Proofmentioning

confidence: 52%

Estimation of the population distribution function using varied L ranked set sampling

Abdallah

2022

RAIRO-Oper. Res.

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Recently, a generalized ranked set sampling (RSS) plan has been provided in the literature called varied L RSS (VLRSS). It is shown that VLRSS encompasses several existing RSS variations and also it efficiently estimates the population mean. In this article, we extend the work and consider estimating the cumulative distribution function (CDF) using VLRSS. Three new CDF estimators are proposed and their asymptotic properties are also theoretically investigated. Taking into account the information supported by the unmeasured sampling units, we also propose a general class of CDF estimators. Using small Monte Carlo experiments, we study the behavior of the proposed CDF estimators with respect to the conventional CDF estimator under RSS. It is found that the conventional RSS-based CDF is outperformed by at least one of VLRSS-based CDF estimators in almost the considered cases. Finally, an empirical example was utilized to illustrate the potential application of the proposed estimators.

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“…By substituting ( 13) and ( 14) in (12), this advocates the consistency of 𝐹 ̂ * (𝑡) which completes the proof.…”

Section: Proofmentioning

confidence: 52%

Estimation of the population distribution function using varied L ranked set sampling

Abdallah

2022

RAIRO-Oper. Res.

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“…Hence, the MSE of ÔSRS s (x 0 ) obtained using ( 12) and (13). From (11) the SRS kernel-based estimator for the OR of the positive tests in disease to the positive tests in health populations within the hth stratum is given by…”

Section: Kernel Estimation Of or Based On Srs In The Hth Stratummentioning

confidence: 99%

“…Using the RSS scheme, most authors such as [7], [5] and [17] have been focused on kernel estimation of PDF. [11] introduced the RSS kernel-based of CDF and compared some properties of this estimator with SRS and empirical estimator.…”

Section: Kernel Estimation Of or Using Rss Scheme For The Hth Stratummentioning

confidence: 99%

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On Kernel-Based Estimator of Odds Ratio Using Different Stratified Sampling Schemes

Eftekharian

Samawi

Rochani

2022

Stat., optim. inf. comput.

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The kernel-based estimator of Cochran Mantel-Haenszel odds ratio based on stratified simple and ranked set sampling is proposed. The expectation and variance of the estimator are analytically obtained. Using a simulation study, the estimator based on stratified ranked set sampling is more efficient than its counterpart based on stratified simple random sampling. Finally, the estimator's performance is investigated by using base deficit data.

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“…There are many kernel functions available in literature however Gaussian is the most famous kernel function, see [2,5,7,8,22,23].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Nadaraya-Watson kernel regression estimators utilizing some non-traditional and robust measures: a numerical application of British food data

Shahzad¹,

Ahmad

Almanjahie

et al. 2023

Hacettepe Journal of Mathematics and Statistics

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In nonparametric regression research, estimation of regression function is a prime concern. Recently, researchers developed some modified Nadaraya-Watson (N-W) regression estimators utilizing robust mean, median and harmonic mean. In this paper, we propose to utilize the additive combination of non-traditional measures i.e. (Hodges-Lehmann, Mid-Range, Tri-Mean, Quartile-Deviation) with the robust minimum covariance determinant (MCD) scale estimator in (N-W) regression estimator. Utilizing these measures, we get some new versions of (N-W) regression estimator. We also attempted to derive the properties of the proposed versions, such as bias, variance, mean square error (MSE), and mean integrated square error (MISE). The proposed estimators are compared with some of the existing estimators available in literature through a simulation study, utilizing two artificial populations. We also incorporated real-life application by taking British food data set denoted as Engel95, and assess the predictive ability of nonparametric regression, based on proposed and existing N-W estimators.

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On estimating the distribution function and odds using ranked set sampling

Cited by 11 publications

References 22 publications

Estimation of the population distribution function using varied L ranked set sampling

Estimation of the population distribution function using varied L ranked set sampling

On Kernel-Based Estimator of Odds Ratio Using Different Stratified Sampling Schemes

Adaptive Nadaraya-Watson kernel regression estimators utilizing some non-traditional and robust measures: a numerical application of British food data

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