{
"@context": "http://schema.org",
"@type": "Dataset",
"@id": "https://doi.org/10.5061/dryad.k8n14",
"url": "https://datadryad.org/stash/dataset/doi:10.5061/dryad.k8n14",
"additionalType": "dataset",
"name": "Data from: The estimation of tree posterior probabilities using conditional clade probability distributions",
"author": {
"name": "Bret Larget",
"givenName": "Bret",
"familyName": "Larget",
"affiliation": {
"@type": "Organization",
"@id": "https://ror.org/01y2jtd41",
"name": "University of Wisconsin-Madison"
},
"@type": "Person"
},
"description": "In this paper I introduce the idea of conditional independence of\n separated subtrees as a principle by which to estimate the posterior\n probability of trees using conditional clade probability distributions\n rather than simple sample relative frequencies. I describe an algorithm\n for these calculations and software which implements these ideas. I show\n that these alternative calculations are very similar to simple sample\n relative frequencies for high probability trees, but are substantially\n more accurate for relatively low probability trees. The method allows the\n posterior probability of unsampled trees to be calculated when these trees\n contain only clades that are in other sampled trees. Furthermore, the\n method can be used to estimate the total probability of the set of sampled\n trees which provides a measure of the thoroughness of a posterior sample.",
"license": "https://creativecommons.org/publicdomain/zero/1.0/legalcode",
"version": "1",
"keywords": "posterior probabilities of trees, Bayesian phylogenetics, conditional clade distributions, independence of separated subtrees",
"inLanguage": "en",
"contentSize": "1242919 bytes",
"datePublished": "2014-01-07T20:49:02Z",
"schemaVersion": "http://datacite.org/schema/kernel-4",
"publisher": {
"@type": "Organization",
"name": "Dryad"
},
"provider": {
"@type": "Organization",
"name": "datacite"
}
}