John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and 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.
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
A.R. Conn, Nick Gould, et al.
Mathematics of Computation
Vladimir Yanovski, Israel A. Wagner, et al.
Ann. Math. Artif. Intell.
Ligang Lu, Jack L. Kouloheris
IS&T/SPIE Electronic Imaging 2002