funHDDC (version 2.0)

slopeHeuristic: Calculate slope heuristic

Description

Compute slope heuristic criterion for number of groups or model selection (seeSchmutz et al. (2017) <hal:01652467> for details).

Usage

slopeHeuristic(mod)

Arguments

mod

A funHDDC object with different number of groups tested or different models.

Value

The index of the best model, among all estimated models.

Details

This function works only if all tested model stored in 'mod' have converged to a solution. If at least one model is written ' -Inf pop<min.individuals' in mod output, an error message will be printed by slopeHeuristic function.

References

- C. Bouveyron and J. Jacques, Model-based Clustering of Time Series in Group-specific Functional Subspaces, Advances in Data Analysis and Classification, vol. 5 (4), pp. 281-300, 2011. - A. Schmutz, C. Bouveyron, J. Jacques, L. Cheze and P. Martin, Clustering multivariate functional data in group-specic functional subspaces, Preprint HAL 01652467, Universit<U+00E9> C<U+00F4>te d'Azur, 2017.

Examples

# NOT RUN {
    library(fda)

    ##Univariate example
    data("trigo")
    basis<- create.bspline.basis(c(0,1), nbasis=25)
    var1<-smooth.basis(argvals=seq(0,1,length.out = 100),y=t(trigo[,1:100]),fdParobj=basis)$fd
    res.uni<-funHDDC(var1,K=2:4)
    slopeHeuristic(res.uni)

    ##Multivariate example
    data("triangle")
    basis <- create.bspline.basis(c(1,21), nbasis=25)
    var1<-smooth.basis(argvals=seq(from=1,to=21,length.out = 101),y=t(triangle[,1:101]),
                        fdParobj=basis)$fd
    var2<-smooth.basis(argvals=seq(from=1,to=21,length.out = 101),y=t(triangle[,102:202]),
                        fdParobj=basis)$fd
    res.multi<-funHDDC(list(var1,var2),K=2:6)
    slopeHeuristic(res.multi)

    
# }
# NOT RUN {
    #An other example on Canada dataset
    library(fda)

    #Clustering the "Canadian temperature" data (Ramsey & Silverman): univariate case
    daybasis65 <- create.fourier.basis(c(0, 365), nbasis=65, period=365)
    daytempfd <- smooth.basis(day.5, CanadianWeather$dailyAv[,,"Temperature.C"], daybasis65,
    fdnames=list("Day", "Station", "Deg C"))$fd

    res.uni<-funHDDC(daytempfd,K=2:6,model="AkjBkQkDk",init="random",threshold=0.2)

    slopeHeuristic(res.uni)

    #Clustering the "Canadian temperature" data (Ramsey & Silverman): multivariate case
    daybasis65 <- create.fourier.basis(c(0, 365), nbasis=65, period=365)
    daytempfd <- smooth.basis(day.5, CanadianWeather$dailyAv[,,"Temperature.C"], daybasis65,
    fdnames=list("Day", "Station", "Deg C"))$fd
    dayprecfd<-smooth.basis(day.5, CanadianWeather$dailyAv[,,"Precipitation.mm"], daybasis65,
    fdnames=list("Day", "Station", "Mm"))$fd

    res.multi<-funHDDC(list(daytempfd,dayprecfd),K=2:4,model="AkjBkQkDk",
    init="random",threshold=0.2)

    slopeHeuristic(res.multi)
    
# }
# NOT RUN {
    
# }