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initialisation: using pictorial structure type models as in [7], we localise all the targets along with the configuration of their parts, for iterations, (a) evolve particles using constrained genetic operators as in EPMCMC filter, (b) the expected likelihood data association provides an efficient solution for data association of each object into the particle weights of the EPMCMC filter. .
Two different tests, Shimodaira–Hasegawa (SH) and Expected Likelihood Weight (ELW), were applied to the two or three resulting topologies for each single or double event, respectively, to further verify the results obtained with RDP3.
c: confidence value (expected likelihood weigth).
cELW = Expected Likelihood Weight, SH = Shimodaira and Hasegawa, n.a = not applicable.
TREE-PUZZLE was used to perform the Expected Likelihood Weight (ELW) test and Shimodaira and Hasegawa (SH) tests.
Results from hypotheses testing based on the three alternative Acanthocephala-sistergroup relationships covered by the present approach using the Expected Likelihood Weight (ELW) test.
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For example, Blangero et al. (2013) assume that σ is known in their derivations of the expected likelihood-ratio-test statistic (ELRT).
Recently, Raffa and Thompson (2014) extended the work of Blangero et al. (2013) by deriving approximations to the ELRT and confidence intervals of the heritability estimate using Taylor series expansions of the expected likelihood-ratio test with respect to the distribution of the eigenvalues of a given pedigree.
The Expected-Likelihood Weights (ELW) of 1,000 local rearrangements were used as confidence values of TreeFinder tree branches.
The Expected-Likelihood Weights (ELW) of 1,000 local rearrangements were used as confidence values of TreeFinder tree branches [ 21].
We compared the likelihood scores of the competing hypotheses (the best tree versus alternative hypothesis) using various criteria (Expected-Likelihood Weight, ELW [ 70]; Shimodaira-Hasegawa [ 71]; Approximately Unbiased, AU [ 72] tests) implemented in Treefinder.
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