Spatial Capture-Recapture provides a comprehensive how-to manual with detailed examples of spatial capture-recapture models based on current technology and knowledge. Spatial Capture-Recapture provides you with an extensive step-by-step analysis of many data sets using different software implementations. The authors' approach is practical - it embraces Bayesian and classical inference strategies to give the reader different options to get the job done. In addition, Spatial Capture-Recapture provides data sets, sample code and computing scripts in an R package. Comprehensive reference on revolutionary new methods in ecology makes this the first and only book on the topic Every methodological element has a detailed worked example with a code template, allowing you to learn by example Includes an R package that contains all computer code and data sets on companion websiteMCMC is not much more difficult for complicated modelsasometimes the hyperparameters need to be sampled using a ... The guiding principle is that it should be chosen large enough so that the posterior for N is not truncated, but it should not be too large due to the ... TD/RJMCMC approaches might appear to have the advantage that one can model N explicitly or consider alternative priors for N.
|Author||:||J. Andrew Royle, Richard B. Chandler, Rahel Sollmann, Beth Gardner|
|Publisher||:||Academic Press - 2013-08-27|