| kCFC | R Documentation | 
Functional clustering and identifying substructures of longitudinal data using kCFC.
kCFC(
  y,
  t,
  k = 3,
  kSeed = 123,
  maxIter = 125,
  optnsSW = list(methodMuCovEst = "smooth", FVEthreshold = 0.9, methodBwCov = "GCV",
    methodBwMu = "GCV"),
  optnsCS = list(methodMuCovEst = "smooth", FVEthreshold = 0.7, methodBwCov = "GCV",
    methodBwMu = "GCV")
)
| y | A list of n vectors containing the observed values for each individual. Missing values specified by  | 
| t | A list of n vectors containing the observation time points for each individual corresponding to y. | 
| k | A scalar defining the number of clusters to define; default 3. Values that define very small clusters (eg.cluster size <=3) will potentially err. | 
| kSeed | A scalar valid seed number to ensure replication; default: 123 | 
| maxIter | A scalar defining the maximum number of iterations allowed; default 20, common for both the simple kmeans initially and the subsequent k-centres | 
| optnsSW | A list of options control parameters specified by  | 
| optnsCS | A list of options control parameters specified by  | 
A list containing the following fields:
| cluster | A vector of levels 1:k, indicating the cluster to which each curve is allocated. | 
| fpcaList | A list with the fpcaObj for each separate cluster. | 
| iterToConv | A number indicating how many iterations where required until convergence. | 
Jeng-Min Chiou, Pai-Ling Li, "Functional clustering and identifying substructures of longitudinal data." Journal of the Royal Statistical Society 69 (2007): 679-699
data(medfly25) 
Flies <- MakeFPCAInputs(medfly25$ID, medfly25$Days, medfly25$nEggs)
kcfcObj <- kCFC(Flies$Ly[1:150], Flies$Lt[1:150], # using only 150 for speed consideration 
                 optnsSW = list(methodMuCovEst = 'smooth', userBwCov = 2, FVEthreshold = 0.90),
                 optnsCS = list(methodMuCovEst = 'smooth', userBwCov = 2, FVEthreshold = 0.70))
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