A review on concomitants of order statistics and its application in parameter estimation under ranked set sampling

Koshti, Rohan D.; Kamalja, Kirtee K.

doi:10.1007/s42952-023-00235-2

Cited by 2 publications

(1 citation statement)

References 139 publications

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“…[2] studied the concomitants of generalized order statistics and dual generalized order statistics from Cambanis family of bivariate distributions with nonzero parameter values. For some other developments for families of bivariate distributions, see, Thomas and Scaria [25], Koshti [18], Kamalja and Koshti [17], Abd Elgawad et al [1], Husseiny et al [16], El-Sherpieny et al [8], Chacko and George [6], George and Chacko [11], Chesneau [7], Koshti and Kamalja [20], Fayomi et al [9,10] and Haj et al [12]. In this paper, we focus on a specific member of the Cambanis family, the CTBU distribution, and thoroughly investigate its statistical properties.…”

Section: Introductionmentioning

confidence: 99%

Cambanis-type Bivariate Uniform Distribution: Properties and Moment Estimation

Koshti,

Kamalja

2024

Computational Journal of Mathematical and Statistical Sciences

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The families of distributions are crucial in statistical modeling, offering a versatile foundation for a variety of applications. The development of bivariate distributions with specific marginal distributions and correlation coefficients is of considerable interest due to its wide-ranging relevance in real-world situations. The range of correlation between variables is an important characterization of the family. The variety of methods of construction of bivariate/multivariate distributions are developed in the literature. The Cambanis family is an important class of multivariate distributions with a wide range of correlation than the traditional families. In this paper, we consider a Cambanis-type bivariate uniform distribution and develop key statistical properties of the Cambanis-type bivariate uniform distribution. We obtain moment estimators of parameters for Cambanis-type bivariate uniform distribution. To evaluate the performance of the estimators, we develop an algorithm to simulate samples from the Cambanis-type bivariate uniform distribution and implement it in the R software. We perform a simulation study to present the performance of moment estimator.

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Section: Introductionmentioning

confidence: 99%

Cambanis-type Bivariate Uniform Distribution: Properties and Moment Estimation

Koshti,

Kamalja

2024

Computational Journal of Mathematical and Statistical Sciences

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On concomitants of generalized order statistics arising from bivariate generalized Weibull distribution and its application in estimation

AL-Zaydi

2024

MATH

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<p>In this research, we studied the concomitants of generalized order statistics from the bivariate generalized Weibull distribution. We derived probability density functions and moments of concomitants of generalized order statistics from the bivariate generalized Weibull distribution. Moreover, utilizing the ranked set sample obtained from this distribution, we computed the best linear unbiased (BLU) estimator of the parameter connected with the study variable (variable of primary interest). Also, a real data application was presented.</p>

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A review on concomitants of order statistics and its application in parameter estimation under ranked set sampling

Cited by 2 publications

References 139 publications

Cambanis-type Bivariate Uniform Distribution: Properties and Moment Estimation

Cambanis-type Bivariate Uniform Distribution: Properties and Moment Estimation

On concomitants of generalized order statistics arising from bivariate generalized Weibull distribution and its application in estimation

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