## Incoherent phyleogeographic inference [reply]

Posted in Statistics, University life with tags , , , , , , , , , on September 29, 2010 by xi'an

“Logical overlap is the norm for the complex models analyzed with ABC, so many ABC posterior model probabilities published to date are wrong.” Alan R. Templeton, PNAS, doi:10.1073/pnas.1009012107

Our letter in PNAS about Templeton’s surprising diatribe on Bayesian inference is now appeared in the early edition, along with Templeton’s reply. This reply is unfortunately missing any novelty element compared with the original paper. First, he maintains that the critcism is about ABC (which is, in case you do not know, a computational technique and not a specific statistical methodology!). Second, he insists on the inappropriate Venn diagram analogy by reproducing the basic identity

$P(A\cup B\cup C) = P(A)+P(B)+P(C)-P(A\cap B)-P(B\cap C)-P(C\cap A)+P(A\cap B\cap C)$

(presumably in case we had lost sight of it!) to argue that using instead

$P(A)+P(B)+P(C)$

is incoherent (hence rejecting Bayes factors, Bayesian model averaging and so on). I am not particularly surprised by this immutable stance, but it means that there is little point in debate when starting from such positions… Our main goal in publishing this letter was actually to stress that the earlier tribune had no statistical ground and I think we achieved this goal.

## Incoherent phylogeographic inference [accepted]

Posted in Statistics, University life with tags , , , , , on August 30, 2010 by xi'an

The letter we submitted to PNAS about Templeton’s surprising diatribe on Bayesian inference has now been accepted:

Title: “Incoherent Phylogeographic Inference”
Tracking #: 2010-08762
Authors: Berger et al.

Dear Prof. Robert,
We are pleased to inform you that the PNAS Editorial Board has given final approval of your letter to the Editor for online publication. The author(s) of the published manuscript have been invited to respond to your feedback. If they provide a response, it may appear online concurrently with your letter.

Now we are looking forward (?) Alan Templeton’s answer, even though I suspect this short letter is not going to have any impact on his views!

## Defence of model-based inference

Posted in Statistics, University life with tags , , , , , on January 13, 2010 by xi'an

A tribune—to which I contributed—about the virtues of statistical inference in phylogeography  just appeared in Molecular Ecology. (The whole paper seems to be available on line as I can access it.) It has been written by 22 (!) contributors in response to Templeton’s recent criticism of ABC (and his defence of Nested Clade Analysis) in the same journal. My contribution to the paper is mostly based on the arguments posted here last March, namely that the paper was confusing ABC (which is a computational method) with Bayesian statistics. The paper as a whole goes beyond a “Bayesian defence” since not all authors are Bayesian. It supports a statistics based approach to phyleogeography, as reported in the abstract

Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics.

This will most presumably fail to end the debate between the proponents and the opponents of model-based inference in phylogenics and elsewhere, but the point was worth making…