A Fast Parameter Estimation Method for Evolutionary Biology


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Documentation for package ‘jaatha’ version 2.2

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jaatha-package Fast estimation of demographic parameters
addFeature Low level function for adding a new feature to a demographic Model
calculateJsfs Calculates the JSFS for data imported with ape
callMs Function to perform simulation using ms
checkType Checks if a variable is of a given type and calls stop() on type mismatch
convertSimResultsToDataFrame Converts simulation results into a data frame that is usable for fitting a glm.
denormalize Convert parameters from Jaatha's internal scale into their natural scale
dm.addGrowth Adds an growth or decline of the population size of one population to a model.
dm.addMigration Add migration/gene flow between two populations to a demographic model
dm.addMutation Adds mutations to a demographic model
dm.addMutationRateHeterogenity Allows the mutation rate on different sites to vary according to a Gamma Distribution.
dm.addOutgroup Adds an outgroup to a demographic model
dm.addParameter Create a parameter that can be used for one or more features
dm.addRecombination Adds recombination events to a demographic model
dm.addSizeChange Adds an instantaneous change of the population size of one population to a model.
dm.addSpeciationEvent Adds a speciation event to a demographic model
dm.addSymmetricMigration Adds symmetric migration between all populations
dm.createDemographicModel Create a basic demographic model
dm.createThetaTauModel Creates a standard "Theta/Tau" demopraphic model.
dm.setMutationModel Defines what mutation model is used for simulations
dm.simSumStats Simulates data according to a demographic model
findBestParInBlock Functions that uses the fitted GLMs to estimate the parameters that have the highest likelihood.
fitGlm Fits a Generalized Linear Model within a block.
fitGlmPoiTransformed Fits a GLM for a summary statistics of type "poisson.transformed" and "poisson.independent"
fitPoiSmoothed Fits a GLM for a summary statistics of type "poisson.smoothed"
getLogFile Gets the current logging file
getLogLevel Gets the current logging level
Jaatha-class The "Jaatha" S4 class saves the basic parameters for a Jaatha estimation procedure
Jaatha.confidenceIntervals Function for calculating bootstrap confidence intervals for jaatha estimates.
Jaatha.getLikelihoods Gives the best estimates after a Jaatha search
Jaatha.getStartingPoints Print Start points
Jaatha.initialize Initialization of a Jaatha estimation for population genetics
Jaatha.initialSearch Search the parameter space for good starting positions
Jaatha.refinedSearch Iterative search for the maximum composite likelihood parameters
Jaatha.setSeqgenExecutable Set the path to the executable for seqgen
normalize Convert parameters from the natural scale into Jaatha's internal scale
runSimulations The function that actually executes the simulations from within Jaatha.
setLogging Function to activate/change logging
simulateWithinBlock This function executes simulations for a number of random parameter values inside a block.