You are not currently logged in.
Access JSTOR through your library or other institution:
A New Method for Estimation of Resource Selection Probability Function
Subhash R. Lele
The Journal of Wildlife Management
Vol. 73, No. 1 (Jan., 2009), pp. 122-127
Stable URL: http://www.jstor.org/stable/40208496
Page Count: 6
You can always find the topics here!Topics: Statistical estimation, Datasets, Preliminary estimates, Natural resource management, Wildlife management, Maximum likelihood estimation, Computer software, Estimators, Algorithms, Natural resources conservation
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Preview not available
Weighted distributions can be used to fit various forms of resource selection probability functions (RSPF) under the useversus-available study design (Lele and Keim 2006). Although valid, the numerical maximization procedure used by Lele and Keim (2006) is unstable because of the inherent roughness of the Monte Carlo likelihood function. We used a combination of the methods of partial likelihood and data cloning to obtain maximum likelihood estimators of the RSPF in a numerically stable fashion. We demonstrated the methodology using simulated data sets generated under the log-log RSPF model and a reanalysis of telemetry data presented in Lele and Keim (2006) using the logistic RSPF model. The new method for estimation of RSPF can be used to understand differential selection of resources by animals, an essential component of studies in conservation biology, wildlife management, and applied ecology.
The Journal of Wildlife Management © 2009 Wiley