Data from: Monte Carlo Strategies for selecting parameter values in simulation experiments

Leigh JW, Bryant D

Date Published: May 18, 2015

DOI: http://dx.doi.org/10.5061/dryad.366j4

 

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Title Scripts and sources for Case study 2
Downloaded 8 times
Description Our C++ implementation of the plant domestication model described in Allaby et al (2008) referenced in our manuscript, along with the Python scripts used to demonstrate our MCMC/importance sampling approach with this model.
Download CaseStudyTwo.tar.bz2 (23.28 Kb)
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Title UPGMA/NJ comparison Python scripts
Downloaded 12 times
Description Scripts used to perform MCMC/importance sampling to compare UPGMA and NJ tree inference methods. The scripts used to compare these methods using a grid search approach, and at random points sampled uniformly from the prior distribution are also included, as well as scripts to compare the grid search/prior sampling to our MCMC+IS method.
Download CaseStudyOne.tar.bz2 (13.10 Kb)
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Title supplement_LeighBryant2015
Downloaded 29 times
Description Updated supplementary information, including details of case study simulations.
Download supplement_LeighBryant2015.pdf (240.7 Kb)
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When using this data, please cite the original publication:

Leigh JW, Bryant D (2015) Monte Carlo Strategies for selecting parameter values in simulation experiments. Systematic Biology 64(5): 741-751. http://dx.doi.org/10.1093/sysbio/syv030

Additionally, please cite the Dryad data package:

Leigh JW, Bryant D (2015) Data from: Monte Carlo Strategies for selecting parameter values in simulation experiments. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.366j4
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