Fits Stickbreaking, Multiplicative and Additive Models to Data


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Documentation for package ‘Stickbreaker’ version 1.0.0

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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.
Chou.data A dataset containing the fitness values for recombinant strains for Methylobacterium extorquens.
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
Khan.data A dataset containing the fitness values for recombinant Escherichia coli bacteria.
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