?? Hello everyone. Just 3 quick questions about MCMCglmm diagnostic tools:
?? 1. When using autocorrelation(), the result I get includes several lines marked as "Lag 1", "Lag 10", "Lag 50", "Lag 100" and so on. In Patrick Lam's fantastic "Convergence Diagnostics" I read this: "The lag k autocorrelation ?k is the correlation between every draw and its kth lag. So, according to this, "Lag 1" is the correlation between one sample and the sample inmediately posterior, "Lag 10" the correlation between a sample and the sample 10 positions after, and so on. Is that right??? 2. In the Course Notes, it says "I usually aim to store 1,000-2,000 iterations and have the autocorrelation between successive stored iterations less than 0.1." Does this mean thin=1,000-2,000? Because in that case, we would be storing every 1,000-2,000 iterations, right??? 3. Apart from autocorr() and trace and density plots, I have seen other diagnostic analyses described for mcmc objects, such as Gelman and Rubin, Geweke, Heidelberg-Lewis or Raftery-Lewis. However, when I try to implement this in my MCMCglmm models, R shows me the message "no applicable method applied to an object of class "MCMCglmm" or other error messages." Are there any diagnostics tools that can be applied to MCMCglmm objects other than the ones mentioned in the Course Notes, autocorr() and plot()?
?? Thank you very much in advance.
?? Iker.
?__________________________________________________________________
?? Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations
?? Joseph Banks Laboratories
?? School of Life Sciences
?? University of Lincoln?? Brayford Campus, Lincoln
?? LN6 7DL
?? United Kingdom
?? https://eric.exeter.ac.uk/repository/handle/10036/3381