Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
We consider the problem of estimating the number of distinct species S in a study area from the recorded presence or absence of species in each of a sample of quadrats. A generalized jackknife estimator of S is derived, along with an estimate of its variance. It is compared with the jackknife estimator for S proposed by b11Heltshe and Forrester (1983, Biometrics39, 1-12) and the empirical Bayes estimator of b14Mingoti and Meeden (1992, Biometrics48, 863-875). We show that the empirical Bayes estimator has the form of a generalized jackknife estimator under a specific model for species distribution. We compare the new estimators of S to the empirical Bayes estimator via simulation. We characterize circumstances under which each is superior. © 2005, The International Biometric Society.
Salvatore Certo, Anh Pham, et al.
Quantum Machine Intelligence
Renu Tewari, Richard P. King, et al.
IS&T/SPIE Electronic Imaging 1996
R.A. Brualdi, A.J. Hoffman
Linear Algebra and Its Applications
J. LaRue, C. Ting
Proceedings of SPIE 1989