2017/02/10 by W.J. Szajnowski, Szajnowski, W. J.
Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference
paper · pdf · doi:10.48550/arxiv.1702.03080
openalex publication_date 2017/02/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.