Inference on overlap coefficients under the Weibull distribution: Equal shape parameter

Al-Saidy, Obaid; Samawi, Hani M.; Al-Saleh, Mohammad Fraiwan

doi:10.1051/ps:2005010

Cited by 17 publications

(11 citation statements)

References 29 publications

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“…The OV L measures are used in many useful applications including, clinical trials (see, Mizuno et al, 2005), and in a comparison of income distributed by race (Weitzman, 1970). Recently, many authors utilized the OV L measures, see Bradley and Piantadosi (1982), Inman and Bradley (1989), Clemons (1996), Reiser and Faraggi (1999), Clemons and Bradley (2000), Mulekar and Mishra (2000), AlSaidy, Samawi and Al-Saleh (2005), Schmid and Schmidt (2006), and Al-Saleh and Samawi (2007).…”

Section: Introductionmentioning

confidence: 99%

On Inference of Overlapping Coefficients in TwoLomaxPopulations Using Different Sampling Methods

Helu

Samawi

2011

Journal of Statistical Theory and Practice

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This paper investigates point and interval estimation for some well-known measures of overlap. Two types of sampling procedures, namely, Simple Random Sample and Ranked Set Sample from two Lomax populations with different shape parameters are considered. Simulation studies are conducted to get insight on the performance of the proposed estimators. Taylor series approximations as well as bootstrap method are used to construct confidence intervals for those measures.

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Section: Introductionmentioning

confidence: 99%

On Inference of Overlapping Coefficients in TwoLomaxPopulations Using Different Sampling Methods

Helu

Samawi

2011

Journal of Statistical Theory and Practice

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“…as in Ref. 3 ) and has been employed in applied research in diverse fields, such as ecology, [4][5][6] economics, 7,8 geology, 3 demography, 9,10 agriculture, 11 genetics and medicine, [12][13][14][15][16][17] social sciences, 18,19 economic theory 7 and so on.…”

Section: Introductionmentioning

confidence: 99%

Inference on the overlap coefficient: The binormal approach and alternatives

Franco-Pereira

Nakas

Reiser

et al. 2021

Stat Methods Med Res

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The overlap coefficient ([Formula: see text]) measures the similarity between two distributions through the overlapping area of their distribution functions. Given its intuitive description and ease of visual representation by the straightforward depiction of the amount of overlap between the two corresponding histograms based on samples of measurements from each one of the two distributions, the development of accurate methods for confidence interval construction can be useful for applied researchers. The overlap coefficient has received scant attention in the literature since it lacks readily available software for its implementation, while inferential procedures that can cover the whole range of distributional scenarios for the two underlying distributions are missing. Such methods, both parametric and non-parametric are developed in this article, while R-code is provided for their implementation. Parametric approaches based on the binormal model show better performance and are appropriate for use in a wide range of distributional scenarios. Methods are assessed through a large simulation study and are illustrated using a dataset from a study on human immunodeficiency virus-related cognitive function assessment.

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“…Mishra et al [7] gave small and large sample properties of the sampling distribution for a function of Δ under the assumption of homogeneity of variances. Recently, several authors including Al-Saidy et al [8], Clemons [9], Dhaker et al [10], Inman and Bradley [11], Jose et al [12], Mulekar and Mishra [13] and Reiser and Faraggi [14] considered this measure.…”

Section: Introductionmentioning

confidence: 99%

On Inference of Overlapping Coefficients in Two Inverse Lomax Populations

Dhaker¹,

Dème²,

El-Adlouni³

2021

JSTA

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Overlapping coefficient is a direct measure of similarity between two distributions which is recently becoming very useful. This paper investigates estimation for some well-known measures of overlap, namely Matusita's measure , Weitzman's measure ∆ and Λ based on Kullback Leibler. Two estimation methods considered in this study are point estimation and Bayesian approach. Two inverse Lomax populations with different shape parameters are considered. The bias and mean square error properties of the estimators are studied through a simulation study and a real data example.

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Inference on overlap coefficients under the Weibull distribution: Equal shape parameter

Cited by 17 publications

References 29 publications

On Inference of Overlapping Coefficients in TwoLomaxPopulations Using Different Sampling Methods

On Inference of Overlapping Coefficients in TwoLomaxPopulations Using Different Sampling Methods

Inference on the overlap coefficient: The binormal approach and alternatives

On Inference of Overlapping Coefficients in Two Inverse Lomax Populations

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