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초록·키워드 목차

The inverted distributions have a wide range of applications in problems related to econometrics, biological sciences, survey sampling, engineering sciences, medical research and life testing problems. In addition, it is employed in financial literature, environmental studies, survival and reliability theory. The main aim of this paper is to define a bivariate generalized inverted Kumaraswamy distribution so that the marginals have generalized inverted Kumaraswamy distributions. And define a bivariate inverted Kumaraswamy distribution as a special case from the bivariate generalized inverted Kumaraswamy distribution. It is observed that the joint probability density function and the joint cumulative distribution function can be expressed in explicit forms. Different properties of this distribution such as marginals, conditional distributions and product moments have been discussed. The maximum likelihood estimates for the unknown parameters of this distribution and their approximate variance-covariance matrix are obtained. Bayesian estimators are also obtained for the unknown parameters of this model explicitly. Some simulations to see the performances of the MLEs are performed. One data analysis also has been performed for illustrative purpose. #Generalized inverted Kumaraswamy distribution #inverted Kumaraswamy distribution #Kumaraswamy distribution #Maximum likelihood Estimation

Abstract
1. INTRODUCTION
2. BIVARIATE GENERALIZED INVERTED KUMARASWAMY DISTRIBUTION
3. BASIC PROPERTIES OF BGIKUM DISTRIBUTION
4. PRODUCT MOMENTS
5. ESTIMATION OF BGIKUM DISTRIBUTION
6. ABSOLUTELY CONTINUOUS BIVARIATE GIKUM
7. DATA ANALYSIS
8. CONCLUSION
REFERENCES

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