Tests of Hypotheses for the Parameters of a Bivariate Geometric Distribution

Many situations in real world cannot be described by a single variable. Simul taneous occurrence of multiple events warrants multivariate distributions. For instance, univariate geometric distribution can represent occurrence of failure of one component of a system. However, to study systems with several com ponents that may have different types of failures, such as twin engines of an airplane or the paired organ in a human body, bivariate geometric distributions are suitable. Bivariate geometric distribution has increasingly important roles in various fields, including reliability and survival analysis. There are different forms of a bivariate geometric distribution. Phatak & Sreehari [1] pro vided a form of the bivariate geometric distribution which is considered here. They introduced a form of probability mass function which take into considera tion of three different types of events. There are other forms which can be seen in Nair & Nair [2], Hawkes [3], Arnold et al. [4] and Sreehari & Vasudeva [5]. Basu & Dhar [6] proposed a bivariate geometric model which is analogous to bivariate exponential model developed by Marshal & Olkin [7]. Characterization results are developed by Sun & Basu [8], Sreehari [9], and Sreehari & Vasudeva [5].