Author: Nicholas M. Fountain-Jones; Craig Packer; Maude Jacquot; F. Guillaume Blanchet; Karen Terio; Meggan E. Craft
Title: Chronic infections can shape epidemic exposure: Pathogen co-occurrence networks in the Serengeti lions Document date: 2018_7_17
ID: 4718pdtk_21
Snippet: Pathogens detected fewer than five times were excluded from this analysis. We fitted all the JSDMs with Bayesian inference, using "Hierarchical Modelling of Species Communities" ("HMSC" Blanchet et al. 2018) . For each analysis, we modeled the response pathogen coexposure matrix using a probit model. In each model we added individual, pride-year (i.e., which pride and year the individual was sampled in) and year sampled as random effects. We util.....
Document: Pathogens detected fewer than five times were excluded from this analysis. We fitted all the JSDMs with Bayesian inference, using "Hierarchical Modelling of Species Communities" ("HMSC" Blanchet et al. 2018) . For each analysis, we modeled the response pathogen coexposure matrix using a probit model. In each model we added individual, pride-year (i.e., which pride and year the individual was sampled in) and year sampled as random effects. We utilized the default priors of the framework (described in full detail in Ovaskainen et al. 2017) and ran the HMSC model twice using 3 million MCMC samples (the first 300 000 of which being burnin). Each run was carried out using a different seed. Visual inspection of MCMC traces were performed to assess convergence. In addition, we made sure that the effective sample size (ESS) of each parameter was > 200.
Search related documents:
Co phrase search for related documents- convergence assess and effective sample size: 1
- convergence assess and ESS effective sample size: 1
- default prior and framework default prior: 1
- effective sample size and ESS effective sample size: 1, 2, 3, 4
Co phrase search for related documents, hyperlinks ordered by date