lobraModelSelection: Evaluation of different spline variants.

In ac-hauschild/LoBrA: Modeling longitudinal Breath Data (LOngitudinal BReath Analysis)

Description

The model selection method evaluates which spline models achieve the best quality among all tested metabolites.

Usage

lobraModelSelection(selectedLDO, potentialSplines = c(), nknots = c(0, 1,
  2), splinetype = "linear", qualityMeasure = c("AIC", "BIC", "logLik"))

Arguments

selectedLDO	LDO containing all selected metabolites to be used for the model selection.
potentialSplines	Vector of all possible knots to be used for the spline modeling.
nknots	Vector of number of spline knots to be used.
splinetype	spline type default is "linear".
qualityMeasure	Vector of quality measures to be used. Possible options are "AIC", "BIC", and "logLik".

Value

square of the in put

Examples

## Not run: 
 
  data(ldoExample)
  potentialSplines <- c(6,8,10,12,14,16)
  
  nknots=c(0,1, 2, 3, 4)
  splinetype="linear"
  qualityMeasure=c("AIC", "BIC", "logLik")
  components <- ldos@selectedPeaks[,"bf"]
  components <- names(components)[components]
  selectedLDO <- selectComponents(ldo, components)
  lobraModelSelectionObject<- lobraModelSelection(selectedLDO, potentialSplines, nknots, splinetype, qualityMeasure)
  # save(modelSelectionObject,file="data/modelSelectionObjectExample.RData")
  
  

ac-hauschild/LoBrA documentation built on May 26, 2019, 3:35 p.m.