This repository contains R codes to reproduce the analyses from our paper 'Inferring animal social networks with imperfect detection' which can be downloaded here. There are two directories. The directory dolphin_case_study contains codes for the real case study on Commerson's dolphin data and is used, among others, to produce Table 1 and Figures 1 and 2. The directory simulations is used to asses the bias in parameter estimates.
We used a Bayesian approach with MCMC simulations to implement our model. We used non-informative uniform U[0,1] prior distributions for all parameters. Convergence was assessed using the Brooks-Gelman-Rubin statistic. Mixing was checked visually by inspecting the chains.
Reference: Gimenez O., L. Mansilla, M.J. Klaich, M.A. Coscarella, S.N. Pedraza, E.A. Crespo (2019). Inferring animal social networks with imperfect detection. Ecological Modelling. 401: 69-74.