Chou.data               A dataset containing the fitness values for
                        recombinant strains for Methylobacterium
                        extorquens.
Khan.data               A dataset containing the fitness values for
                        recombinant Escherichia coli bacteria.
analyze.mult.add.data.batch
                        Analyze batch data generated by
                        'sim.fit.mult.add.data.batch'
analyze.stick.data.batch
                        Analyze batch data generated by
                        'sim.fit.stick.data.batch'
burns.data              A dataset containing the fitness values for
                        recombinant poliovirus viruses.
calc.stick.logLn        Wrapper function so log-likelihood of
                        stickbreaking can be extracted by optimize()
                        function
calculate.posteriors.for.datasets
                        Calculates posterior probabilities for each row
                        of dataset given model
caudle.data             A dataset containing the fitness values for
                        recombinant Escherichia coli bacteria.
estimate.d.MLE          Find MLE of d
estimate.d.RDB          Estimate d using relative distance to boundary
                        (RDB) methods
estimate.d.sequential   Estimate d using sequential method
fit.add.model           Fit the additive model to data
fit.models              Fit all models to data
fit.mult.model          Fit the multiplicative model to data
fit.nnet.multinomial.regression
                        Fit training data to multinomial regression
                        using nnet package
fit.stick.model.given.d
                        Fit the stickbreaking model to data for a given
                        value of d
generate.geno.matrix    Generate genotype matrix for given number of
                        mutations.
generate.geno.weight.matrix
                        Internal simulation function to generate a
                        matrix to weight the genotypes when estimating
                        d and stickbreaking coefficients
regress.back.fitness.vs.effect
                        Linear regression of background fitness against
                        effects
sim.add.data            Simulate data under additive model.
sim.data.calculate.posteriors
                        Simulate data from priors then use to calculate
                        posterior probability of models given data
sim.data.for.mod.selection
                        Simulate data at specified parameter values for
                        doing model selection
sim.data.from.priors.for.mod.selection
                        Simulate data from priors for doing model
                        selection
sim.fit.mult.add.data.batch
                        Simulate fitness data under multiplicative and
                        additive models
sim.fit.stick.data.batch
                        Simulate and fit batch data under stickbreaking
                        model
sim.mult.data           Simulate data under multiplicative model.
sim.partial.data.from.priors.for.mod.selection
                        Simulate partial data from priors for doing
                        model selection
sim.stick.data          Simulate data under stickbreaking model.
summarize.fits.for.posterior.calc
                        Extracts summary statistics from each model
                        needed for posterior calculation
summarize.posteriors.on.simulated.dataset
                        Calculate classification performance on
                        simulated data
