P. ,

P. ,

P. , , p.90

M. References-aitkin, Posterior Bayes factors, J. R. Stat. Soc. B, vol.53, pp.111-142, 1991.

G. Altekar, S. Dwarkadas, J. Huelsenbeck, and F. Ronquist, Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference, Bioinformatics, vol.20, pp.407-415, 2004.

J. Berger and L. Pericchi, The intrinsic Bayes factor for model selection and prediction, J. Am. Stat. Assoc, vol.91, pp.109-122, 1996.

J. P. Bollback, Bayesian model adequacy and choice in phylogenetics, Mol. Biol. Evol, vol.19, pp.1171-1180, 2002.

H. Brinkmann, M. Van-der-giezen, Y. Zhou, G. Poncelin-de-raucourt, and H. Philippe, An empirical assessment of long-branch attraction artefacts in deep eukaryotic phylogenomics, Syst. Biol, vol.54, pp.743-757, 2005.

J. Castresana, Selection of conserved blocks from multiple alignment for their use in phylogenetic analysis, Mol. Biol. Evol, vol.17, pp.540-552, 2000.

S. Chib, Marginal likelihood from the Gibbs output, J. Am. Stat. Assoc, vol.90, pp.1313-1321, 1995.

S. Chib and I. Jeliazkov, Marginal likelihood from the MetropolisHastings output, J. Am. Stat. Assoc, vol.96, pp.270-281, 2001.

J. Felsenstein, Evolutionary trees from DNA sequences: A maximum likelihood approach, J. Mol. Evol, vol.17, pp.368-376, 1981.

B. S. Gaut and P. O. Lewis, Success of the maximum likelihood phylogeny inference in the four taxon case, Mol. Biol. Evol, vol.12, pp.152-162, 1995.

A. Gelman, Simulating normalizing constants: From importance sampling to bridge sampling to path sampling, Stat. Sci, vol.13, pp.163-185, 1998.

A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian data analysis, 2004.

A. Gelman, X. L. Meng, and H. Stern, Posterior predicive assessment of model fitness via realised discrepancies, Stat. Sinica, vol.6, pp.733-807, 1996.

C. J. Geyer, Practical Markov chain Monte Carlo, Stat. Sci, vol.7, pp.473-483, 1992.

C. J. Geyer, Estimating normalizing constants and reweighting mixtures in Markov chain Monte Carlo, 1994.

P. J. Green, Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrika, vol.82, pp.711-732, 1995.
DOI : 10.2307/2337340

C. Han and B. P. Carlin, MCMC methods for computing Bayes factors: A comparative review, Biometrika, vol.82, pp.711-732, 2000.

M. Holder and P. O. Lewis, Phylogenetic estimation: Traditional and Bayesian approaches, Nat. Rev. Genet, vol.4, pp.275-284, 2003.

J. P. Huelsenbeck, B. Larger, and M. E. Alfaro, Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo, Mol. Biol. Evol, vol.21, pp.1123-1133, 2004.
DOI : 10.1093/molbev/msh123

URL : https://academic.oup.com/mbe/article-pdf/21/6/1123/6152458/msh123.pdf

L. And and P. Bayes, , p.207

B. P. Huelsenbeckj, R. E. Larget, F. Miller, and . Ronquist, Potential applications and pitfalls of Bayesian inference of phylogeny, Syst. Biol, vol.51, pp.673-688, 2002.

J. P. Huelsenbeck and F. Ronquist, MrBayes: Bayesian inference of phylogenetic trees, Bioinformatics, vol.17, pp.754-755, 2001.

M. Irestedt, J. Fjeldsa, J. A. Nylander, and P. G. Ericson, Phylogenetic relationships of typical antbirds (Thamnophilidae) and test of incongruence based on Bayes factors, BMC Evol. Biol, vol.4, p.23, 2004.

E. Jaynes, Probability theory. The logic of science, 2003.

H. Jeffreys, Some tests of significance, treated by the theory of probability, Proc. Camb. Phil. Soc, vol.31, pp.203-222, 1935.

D. T. Jones, W. R. Taylor, and J. M. Thornton, The rapid generation of mutation data matrices from protein sequences, CABIOS, vol.8, pp.275-282, 1992.

R. Kass and A. Raftery, Bayes factors and model uncertainty, J. Am. Stat. Assoc, vol.90, pp.773-795, 1995.

B. Larget and D. Simon, Markov chain Monte Carlo algorithms for the Bayesian analysis of phylogenetic trees, Mol. Biol. Evol, vol.16, pp.750-759, 1999.

N. Lartillot and H. Philippe, A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process, Mol. Biol. Evol, vol.21, pp.1095-1109, 2004.
URL : https://hal.archives-ouvertes.fr/lirmm-00108585

X. L. Meng, Posterior predictive p-values, Ann. Stat, vol.22, pp.1142-1160, 1994.
DOI : 10.1214/aos/1176325622

URL : https://doi.org/10.1214/aos/1176325622

X. L. Meng and W. H. Wong, Simulating ratios of normalising constants via a simple identity: A theoretical exploration, Stat. Sinica, vol.6, pp.831-860, 1996.

V. Minin, Z. Abdo, P. Joyce, and J. Sullivan, Performance-based selection of likelihood models for phylogeny estimation, Syst. Biol, vol.52, pp.674-683, 2003.

R. M. Neal, Markov chain sampling methods for Dirichlet process mixture models, J. Comput. Graph. Stat, vol.9, pp.249-265, 2000.

M. A. Newton and A. E. Raftery, Approximating Bayesian inference with the weigthed likelihood bootstrap, J. R. Stat. Soc. B, vol.56, pp.3-18, 1994.

R. Nielsen, Mapping mutations on phylogenies, Syst. Biol, vol.51, pp.729-739, 2001.
DOI : 10.1002/047001153x.g404309

J. A. Nylander, F. Ronquist, J. P. Huelsenbeck, and J. L. Nievesaldrey, Bayesian phylogenetic analysis of combined data, Syst. Biol, vol.53, pp.47-67, 2004.

Y. Ogata, A Monte Carlo method for high dimensional integration, Num. Math, vol.55, pp.137-157, 1989.

A. O'hagan, Fractional Bayes factors for model comparison, J. R. Stat. Soc. B, vol.57, pp.99-138, 1995.

M. Pagel and A. Meade, A phylogenetic mixture model for detecting pattern-heterogeneity in gene sequence or character-state data, Syst. Biol, vol.53, pp.561-581, 2004.

H. Philippe, MUST, a computer package of management utilities for sequences and trees, Nucleic Acid Res, vol.21, pp.5264-5272, 1993.

H. Philippe, N. Lartillot, and H. Brinkmann, Multigene analyses of bilaterian animals corroborate the monophyly of Ecysozoa, Lophotrochozoa and Protostomia, Mol. Biol. Evol, vol.22, pp.1246-1253, 2005.

D. Posada and K. Crandall, Selecting the best-fit model of nucleotide substitution, Syst. Biol, vol.50, pp.580-601, 2001.

A. E. Raftery and S. M. Lewis, Practical Markov chain Monte Carlo]: Comment: One long run with diagnostics: Implementation strategies for Markov chain Monte Carlo, Stat. Sci, vol.7, pp.493-497, 1992.

B. Rannala, Identifiability of parameters in MCMC Bayesian inference of phylogeny, Syst. Biol, vol.51, pp.754-760, 2002.

D. B. Rubin, Bayesianly justifiable and relevant frequency calculations for the applied statistician, Ann. Stat, vol.4, pp.1151-1172, 1984.

G. Schwartz, Estimating the dimension of a model, Ann. Stat, vol.6, pp.461-464, 1978.

S. Stefanovic, D. Rice, and J. Palmer, Long branch attraction, taxon sampling, and the earliest angiosperms: Amborella or monocots?, BMC Evol. Biol, vol.4, p.35, 2004.

M. Stone, Cross-validatory choice and assessment of statistical predictions, J. R. Stat. Soc. B, vol.36, pp.111-147, 1974.

M. Suchard, C. M. Kitchen, J. Sinsheimer, and R. E. Weiss, Hierarchical phylogenetic models for analyzing multipartite sequence data, Syst. Biol, vol.52, pp.649-664, 2003.

M. Suchard, R. Weiss, and J. Sinsheimer, Bayesian selection of continuous-time Markov chain evolutionary models, Mol. Biol. Evol, vol.18, pp.1001-1013, 2001.

J. Sullivan and D. L. Swofford, Are guinea pigs rodents? The importance of adequate models in molecular phylogenetics, J. Mammal. Evol, vol.4, pp.77-86, 1997.

J. Thompson, D. Higgins, and T. Gibson, CLUSTAL W: Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice, Nucleic Acids Res, vol.22, pp.4673-4680, 1994.

I. Verdinelli and L. Wasserman, Computing Bayes factors using a generalization of the Savage-Dickey density ratio, J. Am. Stat. Assoc, vol.90, pp.614-618, 1995.

P. J. Waddell, H. Kishino, and R. Ota, Very fast algorithms for evaluating the stability of ML and Bayesian phylogenetic trees from sequence data, Genome Inform, vol.13, pp.82-92, 2002.

S. Whelan and N. Goldman, A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach, Mol. Biol. Evol, vol.18, pp.691-699, 2001.

Z. Yang, Maximum-likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites, Mol. Biol. Evol, vol.10, pp.1396-1401, 1993.

Z. Yang, Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods, J. Mol. Evol, vol.39, pp.306-314, 1994.

Z. Yang, Among site variation and its impact on phylogenetic analyses, Trends Ecol. Evol, vol.11, pp.367-370, 1996.