title: Uniformly minimum variance unbiased estimation of gene diversity.
abstract: Gene diversity is an important measure of genetic variability in inbred populations. The survival of species in changing environments depends on, among other factors, the genetic variability of the population. In this communication, I have derived the uniformly minimum variance unbiased estimator of gene diversity. The proposed estimator of gene diversity does not assume that the inbreeding coefficient is known. I have also provided the approximate variance of this estimator according to Fisher's method. In addition, I have developed a numerical resampling-based method for obtaining variances and confidence intervals based on the maximum likelihood estimator and the uniformly minimum variance unbiased estimator. Efficiency in estimation of the gene diversity based on these two estimators is discussed. In accordance with the simulation results, I found that the uniformly minimum variance estimator developed in this report is more accurate for estimation of gene diversity than the maximum likelihood estimator.
authors.affiliation: Department of Epidemiology, Box 189, University of Texas, M. D. Anderson Cancer Center, 1515 Holcombe Blvd., Houston, TX 77030, USA. sshete@mdanderson.org
authors.forename: Sanjay
authors.initials: S
authors.lastname: Shete
mesh_terms: D000704:Analysis of Variance; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004950:Esterases / Q000235:genetics; D014644:Genetic Variation; D001467:Hordeum / Q000201:enzymology / Q000235:genetics; D016013:Likelihood Functions
chemical_list: D004950:Esterases