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Finally, the UCLN results show that, quite as expected again, uncorrelated models of rate change performed better than any other approaches considered here.
Using a maximum-likelihood approach, we compared several models of rate heterogeneity among lineages.
Four different models of rate variation are tested in a new program for Bayesian phylogenetic analysis called TreeTime, based on a combination of mitochondrial and nuclear gene sequences.
Likelihood ratio tests comparing null models of rate constancy versus alternative models revealed statistically significant departures from rate constancy across the entire tree (Additional file 1).
Finally, analyses of TConsensus using BEAST indicated that non-autocorrelated models of rate variation fit the data significantly better than a molecular clock (Table 2).
The continued development of molecular clock methodologies over the past two decades has allowed for the estimation of divergence times under more complex models of rate variation.
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Whereas hybrid video coders must undergo significant changes in order to support scalability, our coder only requires a specific wavelet filter for temporal analysis, as well as an adapted bit allocation procedure based on models of rate-distortion curves.
Indeed, models of rate-and-state friction assume an effective normal stress of only a few to several tens of MPa, in order to reproduce slow slip events with recurrence intervals consistent with those of SSEs (e.g., Liu and Rice 2007, 2009).
We also investigated two different models of rates variation among branches: the strict clock and the uncorrelated lognormal-distributed relaxed molecular clock.
As a footnote, while high-yield bond rates have been plummeting, preferred yields have been a model of rate stability.
The matrix was partitioned (i.e., ITS vs. rpL16 intron) with a gamma model of rate heterogeneity and proportion of invariable sites estimated by the program.
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