[R-sig-ME] MCMCglmm diagnostics

[Iker Vaquero Alba]

   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 ρk 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


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