LoBrA (version 1.0)

lobraModelSelection: Evaluation of different spline variants.

Description

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

Usage

lobraModelSelection(
  selectedLDO,
  potentialBreaks = 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.

potentialBreaks

Vector of all possible knots to be used for the spline modeling.

nknots

Vector of number of spline knots to be used. Therefore, 0 ~ no spline, 1 ~ spline with one knot, 2 ~ spline with two knots, etc.

splinetype

spline type default is 'linear'. (Currently only linear is supported.)

qualityMeasure

Vector of quality measures to be used. Possible options are 'AIC', 'BIC', and 'logLik'.

Value

LDOmodelselection Object. For each quality measure the model list contains a list of models for each spline tested. Additionally, the output contains a matrix of qualities for each Spline Component pair. And finally there is a list of breaks for each spline tested.

Examples

# NOT RUN {
# }
# NOT RUN {
  data(LoBraExample)
  potentialBreaks <- c(8,12)
  selectedLDO <- selectComponents(ldo, components)
  ldoSelect<- lobraModelSelection(selectedLDO, potentialBreaks, nknots=c( 1, 2))
  length(ldoSelect@ldo@peaknames)
  
  
# }