User:Carl Boettiger/Notebook/Comparative Phylogenetics/2010/03/20

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  • Bootstrap the fitted models (rather than allow the parameters to be refit, simply evaluate the likelihood of the model under each simulated dataset)
  • Directly evaluate Neyman-Pearson lemma for each pairwise model comparison.
  • Also analyze the bootstrapped likelihoods directly (and without refitting) for each model.

To Do

  • Add a summary function for the likelihood_ratio_bootstrap.R library
  • final wrapper function for infer_niches.R partitioning library
  • More error handling and documentation
  • Example of partitioning Anoles then bootstrapping
  • Bootstrapping likelihoods directly

References on thinking about bootstrapping model comparisons

ouch2ape.R function needs debugging! Works only some of the time. Seems to error on converting back from an ape2ouch conversion.


  • Adding documentation and testing the new bootstrapping functions.
  • New functions make up the bootstrapping likelihood ratio suite:
  1. BM_loglik
  2. my_update
  3. LR_bootstrap
  4. LR_bootstrap_all
  5. plot.LR_boots

The function should be easy to call on a list of ouch models.


Inline documentation provides more details. Functions in this library are contained in the likelihood_ratio_bootstrap.R file.

General Notes

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