Simulation-Based Maximum Likelihood Parameter Estimation.

Jaatha

Jaatha is an estimation method that uses computer simulations to produce maximum-likelihood estimates even when the likelihood function can not be evaluated directly. It can be applied whenever it is feasible to conduct many simulations, but works best when the data is at least approximately Poisson distributed.

Jaatha was originally designed for demographic inference in evolutionary biology. It has optional support for conducting coalescent simulation using the coala R package, but can also be used for different applications.

Jaatha is implemented as an R package and available on CRAN.

Installation

Jaatha can be installed from CRAN using the install.packages command:

install.packages('jaatha')

Usage

The R package includes an introduction vignette that explains how to conduct a jaatha analysis. A second vignette describes how jaatha can be used together with coala for demographic inference.

Further help is provided using R's help system, in particular via ?jaatha, ?create_jaatha_model and ?create_jaatha_data.

Problems

If you encounter problems when using jaatha, please file a bug report or mail to jaatha (at) googlegroups (dot) com.

References

Jaatha's original algorithm is described in the publication:

L. Naduvilezhath, L.E. Rose and D. Metzler: Jaatha: a fast composite-likelihood approach to estimate demographic parameters. Molecular Ecology 20(13):2709-23 (2011).

The revised version of the algorithm that is implemented in this package is described in:

L.A. Mathew, P.R. Staab, L.E. Rose and D. Metzler: Why to account for finite sites in population genetic studies and how to do this with Jaatha 2.0. Ecology and Evolution (2013).

Development

Jaatha is developed openly on GitHub. Feel free to open an issue there if you encounter problems using Jaatha or have suggestions for future versions.

The current development version can be installed using:

devtools::install_github('statgenlmu/jaatha')