Nothing
data("alligator")
alligator_data <- process_measurements(alligator,
pos = "Vertebra")
# Compute PCOs
alligator_PCO <- svdPCO(alligator_data)
# Evaluate model performance (R2) given supplied
# breakpoints for a continuous model
modelperf(alligator_PCO, scores = 1:3,
bps = c(7, 15, 20), cont = TRUE)
plotsegreg(alligator_PCO, scores = 1:3,
bps = c(7, 15, 20), cont = TRUE)
## See also `?calcmodel` for use with a single model
# 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)
# Evaluate support for each model and rank
supp <- modelsupport(bestresults)
# Evaluate model performance (R2) for best model
# as chosen by BIC
modelperf(alligator_PCO, scores = 1:4,
modelsupport = supp,
criterion = "bic", model = 1)
# Plot that model for the first PCO score
plotsegreg(alligator_PCO, scores = 1:4,
modelsupport = supp,
criterion = "bic", model = 1)
## See `?simregions` for use with simulated data
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