Abstract
This paper attempts to introduce an estimate of a bivariate survival function F¯ as well as its marginals based on a random sample (X1,Y1),....(Xn,Yn) from F¯ when F¯ is known to belong to a particular class of distributions called positive quadrant dependent (PQD) class.The constriants which define PQD class make finding a nonparametric maximum likelihood estimator among PQD class extremely difficult.In this paper we elect a form of minimum distance approach for estimating F¯.To make numeerical computations feasible, we choose not to minimize the distance, sup norm, between the empirical survival function F¯n and the entire PQD class.Rather our estimator minimizes the distance to F¯n among distributions that places positive mass only on the subset of the observed sample values and satisfy the constraint PQD.
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