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This function computes the maximum likelihood estimates of the parameters of the Neutral model, using the Etienne Sampling Formula
● Data Source:
CranContrib
● Keywords:
● Alias: maxLikelihood.ESF
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Using this function it is possible to generate a community dataset consisting of two separate abundance vectors for each guild, where the data generated adhere to the Guilds model.
● Data Source:
CranContrib
● Keywords:
● Alias: generate.Guilds
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This function generates community data under the standard neutral model of biodiversity, using the urn scheme as described in Etienne 2005
● Data Source:
CranContrib
● Keywords:
● Alias: generate.ESF
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This function estimates the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y and J. The expected species abundance distribution is approximated by first drawing px from equation 9. Because the abundance distributions of the two guilds are independent, the distributions can now be obtained using equation 6 in Etienne and Alonso 2005. Because drawing from the beta distribution and equation 3 is inherently stochastic, this function returns the average over a specified number of replicates.
● Data Source:
CranContrib
● Keywords:
● Alias: expected.SAD.Guilds.Conditional
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This function computes the maximum likelihood estimates of the parameters of the guilds model, conditioned on guild size.
● Data Source:
CranContrib
● Keywords:
● Alias: maxLikelihood.Guilds.Conditional
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This function calculates the likelihood of the Etienne Sampling Formula, provided abundance data and parameter values.
● Data Source:
CranContrib
● Keywords:
● Alias: logLikelihood.ESF
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logLikelihood.Guilds
(Package: GUILDS) :
Likelihood of the Guilds sampling formula
This function calculates the likelihood of the guilds model, provided abundance data and parameter values.
● Data Source:
CranContrib
● Keywords:
● Alias: logLikelihood.Guilds
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This function calculates the expected species abundance distribution of the standard neutral model given theta, m and J, sensu equation 6 from Etienne and Alonso (2005).
● Data Source:
CranContrib
● Keywords:
● Alias: expected.SAD
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GUILDS-package
(Package: GUILDS) :
Package implementing the Guilds sampling formula for the Neutral Theory of Biodiversity
The GUILDS package contains a number of sampling formula's being the Etienne Sampling Formula (Etienne 2005), the GUILDS sampling formula (Janzen et al. 2014) and the GUILDS sampling formula conditioned on guild Size (Janzen et al. 2015). Furthermore it contains functions to generate data given the guilds model, with or without conditioning on guild size. C++ Code to obtain Sterling numbers of the first kind was adopted from the Tetame program by Jabot et al. (2008).
Updates
Version 1.2.1 : Updated the User manual
Version 1.2 : fixed memory leak issues by adding extra vector access checks
Version 1.2 : fixed memory leak issues by introducing vectors in KDA code
Version 1.2 : renamed logLik to avoid shadowing of the function logLik in the package stats
Version 1.1 : removed malloc header from KDA code
● Data Source:
CranContrib
● Keywords: Etienne Sampling Formula, GUILDS, Neutral Theory
● Alias: GUILDS
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This function estimates the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y and J. The expected species abundance distribution is approximated by first drawing px from a beta distribution (equation 4 in Janzen et al. 2014). Then, guild sizes are drawn using equation 3 in Janzen et al. 2014. Because the abundance distributions of the two guilds are independent, the distributions can now be obtained using equation 6 in Etienne and Alonso 2005. Because drawing from the beta distribution and equation 3 is inherently stochastic, this function returns the average over a specified number of replicates.
● Data Source:
CranContrib
● Keywords:
● Alias: expected.SAD.Guilds
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