[numeric]: Long computations can take several days. So it is possible to save the object ClusterLongData3d on which works kml3d once in a while. saveFreq defines the frequency of the saving process. The ClusterLongData3d is saved every saveFreq clustering calculations. The object is saved in the file objectName.Rdata in the curent folder.

[numeric]: Set a limit to the number of iteration if convergence is not reached.

[character]: the calculation of quality criterion can not be done if some value are missing. imputationMethod define the method use to impute the missing value. See imputation for detail.

[character]: name of the distance used by k-means. If the distanceName is "euclidean3d", a compiled optimized version specificaly design for joint-trajectories version is used. Otherwise, the function define in the slot distance is used.

[numeric]: If distanceName="minkowski", this define the power that will be used.

[numeric <- function(trajA,trajB)]: function that computes the distance between two trajectories. If no function is specified, the Euclidian distance with Gower adjustment (to deal with missing value) is used.

[numeric <- function(vector(numeric))]: k-means algorithm computes the centers of each cluster. It is possible to personalize the definition of "center" by defining a function "centerMethod". This function should take a vector of numeric as argument and return a single numeric -the center of the vector-.

[character]: specifies the starting condition. Should be one of "randomAll", "randomK", "maxDist", "kmeans++", "kmeans+", "kmeans-" or "kmeans–" (see initializePartition for details). It also could take two specifics values: "all" stands for c("maxDist","kmeans-") then an alternance of "kmeans–" and "randomK" while "nearlyAll" stands for "kmeans-" then an alternance of "kmeans–" and "randomK".

[numeric]: set the maximum number of quality criterion that are display on the graph (since displaying a high criterion number an slow down the overall process, the default value is 100).

[logical]: if TRUE, then the data will be automaticaly scaled (using the function scale with default values) before the execution of k-means on joint trajectories. Then the data will be restore (using the function restoreRealData) just before the end of the function kml3d. This option has no effect on kml.