Software

Modelling Population Dynamics

Computer Code and data by chapter for:

Newman, K., Buckland, S.T., Morgan, B.J.T., King, R., Borchers, D.L., Cole, D., Besbeas, P., Gimenez, O., Thomas, L. 2014. Modelling Population Dynamics.

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R-package release

synlik: Synthetic Likelihood methods for intractable likelihoods

Authors: Matteo Fasiolo and Simon Wood

Synthetic Likelihood (SL) is a statistical methodology, introduced by Wood (2010), which can be used to do inference for models where the likelihood function is unavailable or intractable. SL is general-purpose in the sense that, as long as the user is able to simulate data from his model, he should be able to fit it. For this reason, the synlik R-package puts very few limitations on the model being fitted: the user has simply to provide a simulator and (optionally) a function that transforms that data into summary statistics.

The package has been written with attention to computational efficiency and most of the functions provided support computation on
multiple cores. At the moment synlik includes a flexible framework and the set of tools described by Wood (2010). In the future the package will be often updated and improved by the addition of new statistical methods and tools developed during my PhD.

Available on CRAN: http://cran.r-project.org/web/packages/synlik/index.html

and github: http://mfasiolo.github.io/synlik_release/

References:
– Matteo Fasiolo, Simon Wood. An introduction to synlik (2014). R package version 0.1.0.

URL: http://cran.r-project.org/web/packages/synlik/vignettes/synlik.html

– Simon N Wood. Statistical inference for noisy nonlinear ecological dynamic systems. Nature, 466(7310):1102–1104, 2010.

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Distance: Software for design and analysis of distance sampling surveys of wildlife populations

Stand-alone software, and a set of R packages

For more information, see the Distance home page:

http://distancesampling.org/

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Stat-JR Software

A new version of Stat-JR software together with practicals and non-ecology practicals can be found here.

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