MorphoRegions (version 0.1.0)

modelselect: Select the best models

Description

modelselect() narrows down the search for the best model by identifying the best model for each number of regions as determined by its residual sums of squares (RSS).

Usage

modelselect(results, scores = NULL)

Value

A regions_modelselect object, which contains information about the best models for each number of regions extracted from results.

Arguments

results

a regions_results object; the output of a call to calcregions() or addregions().

scores

numeric; a vector corresponding to the indices of the PCOs the \(R^2\) of which will be used to determine the best model for each number of regions. If NULL, the default, all PCOs used included in the fitting will be used.

See Also

modelsupport() for computing statistics that describe the support of each model using information criteria; modelperf() for computing fit statistics for selected models.

Examples

data("alligator")

alligator_data <- process_measurements(alligator,
                                       pos = "Vertebra")

# Compute PCOs
alligator_PCO <- svdPCO(alligator_data)

# Fit segmented regression models for 1 to 7 regions
# using PCOs 1 to 4 and a continuous model with a
# non-exhaustive search
regionresults <- calcregions(alligator_PCO,
                             scores = 1:4,
                             noregions = 7,
                             minvert = 3,
                             cont = TRUE,
                             exhaus = FALSE,
                             verbose = FALSE)

regionresults

# For each number of regions, identify best
# model based on minimizing RSS
bestresults <- modelselect(regionresults)
bestresults

# Evaluate support for each model and rank models
supp <- modelsupport(bestresults)
supp

# 5 regions best based on AICc; 6 regions based on BIC