Presence-Only Data and the EM Algorithm
نویسندگان
چکیده
منابع مشابه
Presence-only data and the em algorithm.
SUMMARY In ecological modeling of the habitat of a species, it can be prohibitively expensive to determine species absence. Presence-only data consist of a sample of locations with observed presences and a separate group of locations sampled from the full landscape, with unknown presences. We propose an expectation-maximization algorithm to estimate the underlying presence-absence logistic mode...
متن کاملAn EM Algorithm for Estimating the Parameters of the Generalized Exponential Distribution under Unified Hybrid Censored Data
The unified hybrid censoring is a mixture of generalized Type-I and Type-II hybrid censoring schemes. This article presents the statistical inferences on Generalized Exponential Distribution parameters when the data are obtained from the unified hybrid censoring scheme. It is observed that the maximum likelihood estimators can not be derived in closed form. The EM algorithm for computing the ma...
متن کاملInference from presence-only data; the ongoing controversy.
Presence-only data abounds in ecology, often accompanied by a background sample. Although many interesting aspects of the species' distribution can be learned from such data, one cannot learn the overall species occurrence probability, or prevalence, without making unjustified simplifying assumptions. In this forum article we question the approach of Royle et al. (2012) that claims to be able t...
متن کاملOnline EM Algorithm for Latent Data Models
In this contribution, we propose a generic online (also sometimes called adaptive or recursive) version of the Expectation-Maximisation (EM) algorithm applicable to latent variable models of independent observations. Compared to the algorithm of Titterington (1984), this approach is more directly connected to the usual EM algorithm and does not rely on integration with respect to the complete d...
متن کاملEstimation of the Parameters of the Lomax Distribution using the EM Algorithm and Lindley Approximation
Estimation of statistical distribution parameter is one of the important subject of statistical inference. Due to the applications of Lomax distribution in business, economy, statistical science, queue theory, internet traffic modeling and so on, in this paper, the parameters of Lomax distribution under type II censored samples using maximum likelihood and Bayesian methods are estimated. Wherea...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Biometrics
سال: 2008
ISSN: 0006-341X
DOI: 10.1111/j.1541-0420.2008.01116.x