Fitting, simulating and generally exploring the distribution of fitness effects from MA studies
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Distributions of fitness effects

This is a work-in-progress package, aiming to provide functions for users to fit existing and new models of the distribution of fitness effects from data arising from mutation accumulation experiments

As of Jan 2015, everything here is bleedingly alpha and will almost certainly change in the future.

Package design

Simulating MA experiments

Functions starting rma_*() simulate the fitness effects arising from a mutation accumulation study, in which the fitness-effects are distributed according to a * distribution. Current options are:

rma_normal()
rma_gamma()
rma_FGM()

rma_FGM() simulates mutations under a paramaterization of Fisher's Geometric Model (by default fitness is determined by the squared distance form the origin, user-defined fitness functions are allowed).

Likelihood for observed data

Functions starting dma_*() calculate likelihood (densities) under the normal or gamma distributed models:

dma_gamma()
dma_normal()

There are also ML fitting functions, fit_ma*(), which are... a work in progress

Miscellaneous functions

BM() calculates Bateman-Mukai (method of moments) estimators, moments_gamma() calculates the mean and variance of a given Gamma distribution, moments_FGM() estimates the mean, variance, skewness and proportion of beneficial mutations via simulation.