detect (version 0.4-0)

detect-package: Analyzing Wildlife Data with Detection Error

Description

Models for analyzing site occupancy and count data models with detection error, including single-visit based models, conditional distance sampling and time-removal models. Package development was supported by the Alberta Biodiversity Monitoring Institute (www.abmi.ca) and the Boreal Avian Modelling Project (borealbirds.ca).

Details

svocc: single visit occupancy model (Lele et al. 2011, Moreno et al. 2010).

svabu: single visit abundance model based on conditional maximum likelihood (Solymos et al. 2012, Solymos and Lele 2016).

cmulti: conditional multinomial maximum likelihood estimation for removal and (point count) distance sampling, efficient and flexible setup for varying methodologies (Solymos et al. 2013).

References

Moreno, M. and Lele, S. R. 2010. Improved estimation of site occupancy using penalized likelihood. Ecology, 91, 341--346.

Lele, S.R., Moreno, M. and Bayne, E. 2011. Dealing with detection error in site occupancy surveys: What can we do with a single survey? Journal of Plant Ecology, 5(1), 22--31.

Solymos, P., Lele, S. R and Bayne, E. 2012. Conditional likelihood approach for analyzing single visit abundance survey data in the presence of zero inflation and detection error. Environmetrics, 23, 197--205.

Solymos, P., Matsuoka, S. M., Bayne, E. M., Lele, S. R., Fontaine, P., Cumming, S. G., Stralberg, D., Schmiegelow, F. K. A. & Song, S. J., 2013. Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation. Methods in Ecology and Evolution, 4, 1047--1058.

Supporting info, including a tutorial for the above paper: http://dcr.r-forge.r-project.org/qpad/

Solymos, P., Lele, S. R. 2016. Revisiting resource selection probability functions and single-visit methods: clarification and extensions. Methods in Ecology and Evolution, 7, 196--205.