PopVar (version 1.3.0)

internal: Internal functions

Description

Internal functions generally not to be called by the user.

Usage

par_position(crossing.table, par.entries)
par_name(crossing.mat, par.entries)
tails(GEBVs, tail.p)
maf_filt(G)
XValidate_nonInd(
  y.CV = NULL,
  G.CV = NULL,
  models.CV = NULL,
  frac.train.CV = NULL,
  nCV.iter.CV = NULL,
  burnIn.CV = NULL,
  nIter.CV = NULL
)
XValidate_Ind(
  y.CV = NULL,
  G.CV = NULL,
  models.CV = NULL,
  nFold.CV = NULL,
  nFold.CV.reps = NULL,
  burnIn.CV = NULL,
  nIter.CV = NULL
)
calc_marker_effects(
  M,
  y.df,
  models = c("rrBLUP", "BayesA", "BayesB", "BayesC", "BL", "BRR"),
  nIter,
  burnIn
)

Arguments

crossing.table

The crossing table.

par.entries

The parent entries.

crossing.mat

The crossing matrix.

GEBVs

The genomic estimated breeding values.

tail.p

The proportion from the population to select.

G

The marker genotypes

y.CV

The phenotypes for cross-validation.

G.CV

The marker genotypes for cross-validation.

models.CV

The models for cross-validation.

frac.train.CV

The fraction of data to use as training data in cross-validation.

nCV.iter.CV

The number of iterations of cross-validation.

burnIn.CV

The burn-in number for cross-validation.

nIter.CV

The number of iterations for Bayesian models in cross-validation.

nFold.CV

The number of folds in k-fold cross-validation.

nFold.CV.reps

The number of replications of k-fold cross-validation.

M

The marker matrix.

y.df

The phenotype data.

models

The models to use.

nIter

The number of iterations.

burnIn

The burn-in rate.