RMark : an R Interface for analysis of capture-recapture data with MARK

By Jeffrey L. Laake. 2013

806 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6538f052fb4cd286c41fc81a7a60fa079c823e7d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Olivier Gimenez
2. Jürgen Niedballa
3. J. Gaillard
4. A. Courtiol
5. A. Wilting
6. E. Cam
7. R. Sollmann
8. J. Lebreton

Citations in the corpus

• camtrapR: an R package for efficient camera trap data management (2016, methodology): “For non-spatial capture – recapture analyses, the function can also return an RMark data frame, containing only individual-by-occasion information without the spatial component.”
• Individual heterogeneity and capture–recapture models: what, why and how? (2018, methodology): “For the sake of illustration, we simulate data in R that we analyze 1) in a frequentist framework using maximum likelihood methods with program MARK (White and Burnham 1999) called from R using the package RMark (Laake 2013; alternatively, see the R package marked by Laake et al. 2013) and E-SURGE (”