2013
DOI: 10.5539/ijsp.v2n3p1
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Estimation of the Parameters of Bivariate Normal Distribution with Equal Coefficient of Variation Using Concomitants of Order Statistics

Abstract: To provide an optimum estimator for the parameters, the use of priori information has a crucial role in univariate as well as bivariate distributions. One such prior information is to utilize the knowledge on coefficient of variation in the inference problems. In the past plenty of work was carried out regarding the estimation of the mean μ of the normal distribution with known coefficient of variation. Also inference about the parameters of bivariate normal distribution in which X and Y have the equal (known)… Show more

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Cited by 2 publications
(2 citation statements)
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“…Estimating the location parameter µ of the exponential distribution with known coecient of variation using the technique of ranked set sampling are discussed by Irshad and Sajeevkumar (2011). Also Sajeevkumar and Irshad (2011) discussed estimation of the location parameter µ of the exponential distribution with known coecient of variation using censored samples.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…Estimating the location parameter µ of the exponential distribution with known coecient of variation using the technique of ranked set sampling are discussed by Irshad and Sajeevkumar (2011). Also Sajeevkumar and Irshad (2011) discussed estimation of the location parameter µ of the exponential distribution with known coecient of variation using censored samples.…”
Section: Introductionmentioning
confidence: 99%
“…Some of the articles which appeared in the literature regarding the estimation of parameters of bivariate normal distribution with coecient of variation as prior information are due to Azen and Reed (1973) and Gupta and Subramanian (1998). Recently Sajeevkumar and Irshad (2013) studied the problem of estimation of parameters of bivariate normal distribution under the assumption that the marginal distributions of random variables X and Y have the same coecients of variation.…”
Section: Introductionmentioning
confidence: 99%