net.maizegenetics.analysis.modelfitter

Interface ForwardRegression

All Known Implementing Classes:

AbstractForwardRegression, AdditiveModelForwardRegression, AdditiveResidualForwardRegression

public ForwardRegression

Method Detail

fittedModel

java.util.List<kotlin.Array[]> fittedModel()

Returns:

org.jetbrains.dokka.NodeRenderContent@43b7e70a: a list of terms in the model. Each item in the list is an an array whose first element is a Position. The second element an Integer equal to the site index of the term. The third element is a Double equal to the p-value for the term.

fitModelForSubsample

void fitModelForSubsample(kotlin.Array[] subSample,
                          int iteration)

Parameters:

subSample - an array of the sample indices to included in the subsample. Indices can be repeated, for example for bootstrap samples.

iteration - the iteration or the sequential index of models fit

fitModel

void fitModel()

phenotype

Phenotype phenotype()

resetModel

void resetModel(int phenotypeIndex,
                double enterLimit,
                int maxVariants)

This method resets the fitted model to the base model and sets the index of the trait to be fit.

Parameters:

enterLimit - the maximum p-value allowed for a term entering the model

maxVariants - the maximum number of variants that will be fit in a model

columnLabels

static java.lang.String[] columnLabels()