Title: Estimators of the correlation coefficient in the bivariate exponential distribution,
Abstract: A finite-support constraint on the parameter space is used to derive a lower
bound on the error of an estimator of the correlation coefficient in the
bivariate exponential distribution. The bound is then exploited to examine
optimality of three estimators, each being a nonlinear function of moments of
exponential or Rayleigh observables. The estimator based on a measure of cosine
similarity is shown to be highly efficient for values of the correlation
coefficient greater than 0.35; for smaller values, however, it is the
transformed Pearson correlation coefficient that exhibits errors closer to the
derived bound.