Published on 01 January 2016

Supplement 1. Program code for maximum likelihood estimation of neutral model parameters for multiple samples of species abundances using the two-stage approach described in the paper.

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Rampal S. Etienne

Description

File List ML-TwoStage.zip -- (all files at once) logKDA1.gp loglikSAD1a.gp MLthetaISADstage2.gp MLthetaISADtwostage.gp Description ML-TwoStage.zip contains files to calculate the parameters that maximize the likelihood of a particular species-abundance data set in multiple samples where dispersal limitation may differ across samples. It runs under PARI/gp which can be downloaded for free from http://pari.math.u-bordeaux.fr/download.html Put all files in the PARI/examples folder. Then open “MLthetaISADtwostage.gp” in any editor and read the instructions (where the species-abundance data should be put) and start the program by typing read("MLthetaISADtwostage.gp") at the PARI/GP prompt, or by \r MLthetaISADtwostage.gp, depending on what version of PARI/GP you are using. The output will be, for each sample: the sample number, the sample size, the number of species in the sample, Fisher's alpha, the θ-value obtained by maximizing the likelihood given by the Ewens sampling formula, the Ewens maximum-likelihood itself, the θ-value obtained by the two-stage approach, the m-value obtained by the two-stage approach, the I-value obtained by the two-stage approach, and the Etienne (2005) likelihood for these parameter values if this sample was considered in isolation. Note: the total likelihood will not be the sum of the sample likelihoods, because the order of the species matters in the multple sample case.

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Metrics

Dataset Index

2.0

FAIR Score

81%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

Assigned Domain

Subfield

Statistics and Probability

Field

Mathematics

Domain

Physical Sciences

Confidence Score

33%

Source

Scholar Data Model

Keywords

Environmental ScienceEcologyFOS: Biological sciences

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00