rubias | R Documentation |
Read the "rubias-overview" vignette for information on data input formats and how to use the package
rubias
main high-level functionsThe following functions are wrappers, designed for user-friendly input and useful output:
infer_mixture
is used to perform genetic stock identification.
Options include standard MCMC and the parametric bootstrap bias correction.
self_assign
does simple self-assignment of individuals in a reference data set
to the various collections in the reference data set.
assess_reference_loo
does leave-one-out based simulations to predict how
accurately GSI can be done.
assess_reference_mc
uses Monte-Carlo cross-validation based simulations
to predict how accurately GSI can be done.
assess_pb_bias_correction
attempts to demonstrate how much (or little)
improvement can be expected from the parametric bootstrap correction given a particular
reference data set.
See the vignette.
alewife
, blueback
, and chinook
are
genetic data sets that are useful for playing around with rubias and testing it
out.
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