View source: R/train.peaksplines.R
getOptimalSpline | R Documentation |
The method calculates which spline model and parameters worked best with respect to the median of the specified quality measure. The median is calculated among all component models.
getOptimalSpline( lobraModelSelectionObject, qualityMeasure = "AIC", summeryfun = stats::median )
lobraModelSelectionObject |
LDOmodelselection created by the 'lobraModelSelection' function. It stores all evaluated Spline models to chose from. |
qualityMeasure |
Quality measure to be used to select the optimal spline. |
summeryfun |
Define the Summery function to be used. Default value is set to stats::median. Other possible functions would be mean, for instance. |
The function returns a 'lobraModelSelectionObject' that contains the optimal model according to the specified quality measure. @seealso plot.modelSelectionEvaluation
## Not run: data(LoBraExample) selectedLDO <- selectComponents(ldo, components) potentialBreaks=c(8, 12) nknots=c(1, 2) qualityMeasure=c("AIC", "BIC") ldoSelect<- lobraModelSelection(selectedLDO, potentialBreaks, nknots, qualityMeasure) optimalAIC<-getOptimalSpline(ldoSelect, qualityMeasure="AIC", summeryfun=stats::median) message(optimalAIC@breaks); optimalBIC<-getOptimalSpline(ldoSelect, qualityMeasure="BIC", summeryfun=base::mean) hist(unlist(optimalBIC@quality));
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