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Notes on the birth–death prior with fossil calibrations for Bayesian estimation of species divergence times

Overview of attention for article published in Philosophical Transactions of the Royal Society B: Biological Sciences, July 2016
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Title
Notes on the birth–death prior with fossil calibrations for Bayesian estimation of species divergence times
Published in
Philosophical Transactions of the Royal Society B: Biological Sciences, July 2016
DOI 10.1098/rstb.2015.0128
Pubmed ID
Authors

Mario dos Reis

Abstract

Constructing a multi-dimensional prior on the times of divergence (the node ages) of species in a phylogeny is not a trivial task, in particular, if the prior density is the result of combining different sources of information such as a speciation process with fossil calibration densities. Yang & Rannala (2006 Mol. Biol. Evol 23, 212-226. (doi:10.1093/molbev/msj024)) laid out the general approach to combine the birth-death process with arbitrary fossil-based densities to construct a prior on divergence times. They achieved this by calculating the density of node ages without calibrations conditioned on the ages of the calibrated nodes. Here, I show that the conditional density obtained by Yang & Rannala is misspecified. The misspecified density can sometimes be quite strange-looking and can lead to unintentionally informative priors on node ages without fossil calibrations. I derive the correct density and provide a few illustrative examples. Calculation of the density involves a sum over a large set of labelled histories, and so obtaining the density in a computer program seems hard at the moment. A general algorithm that may provide a way forward is given.This article is part of the themed issue 'Dating species divergences using rocks and clocks'.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 25%
Student > Master 5 18%
Professor 4 14%
Student > Bachelor 3 11%
Student > Doctoral Student 2 7%
Other 5 18%
Unknown 2 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 50%
Biochemistry, Genetics and Molecular Biology 5 18%
Earth and Planetary Sciences 5 18%
Computer Science 1 4%
Unknown 3 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2016.
All research outputs
#15,090,466
of 25,371,288 outputs
Outputs from Philosophical Transactions of the Royal Society B: Biological Sciences
#5,615
of 7,096 outputs
Outputs of similar age
#209,997
of 377,256 outputs
Outputs of similar age from Philosophical Transactions of the Royal Society B: Biological Sciences
#69
of 95 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,096 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.7. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.