Fit models to data from unmarked animals using Stan. Uses a similar interface to the R package 'unmarked', while providing the advantages of Bayesian inference and allowing estimation of random effects.
Zipkin, E.F., Sillett, T.S., Grant, E.H.C., Chandler, R.B., and Royle, J.A. (2014) Inferences from count data using multi-state population models: a comparison to capture-recapture approaches. Ecology and Evolution. 4: 417-426.
Rossman R., Yackulic C., Saunders S.P., Reid J., Davis R., and Zipkin E.F. 2016. Dynamic N-occupancy models: estimating demographic rates and local abundances from detection-nondetection data. Ecology. 97: 3300-3307.
Zipkin E.F., Rossman S., Yackulic C., Wiens J.D., Thorson J.T., Davis R.J., and Grant E.H.C. 2017. Integrating count and detection-nondetection data to model population dynamics. Ecology. 98: 1640-1650.
Zipkin E.F., Thorson J.T., See K., Lynch H.J., Grant E.H.C., Kanno Y., Chandler R.B., Letcher B.H., and Royle J.A. 2014. Modeling structured population dynamics using data from unmarked individuals. Ecology. 95: 22-29.
Abundance models for avian point counts that use distance and time-removal sampling to estimate detection probabilities.
Add a description, image, and links to the n-mixture-model topic page so that developers can more easily learn about it.
To associate your repository with the n-mixture-model topic, visit your repo's landing page and select "manage topics."