kml3d (version 2.3)

parKml3d: ~ Function: parKml3d ~

Description

parKml3d is a constructor of object ParKml that provide adequate default value for the use of function kml3d.

Usage

parKml3d(saveFreq = 100, maxIt = 200, imputationMethod = "copyMean",
    distanceName = "euclidean3d", power = 2, distance = function() {
    }, centerMethod = meanNA, startingCond = "nearlyAll", nbCriterion =100,scale=TRUE)

Arguments

saveFreq

[numeric]: Long computations can take several days. So it is possible to save the object ClusterLongData3d on which works kml3d once in a while.

maxIt

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

imputationMethod

[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 imputati

distanceName

[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 defin

power

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

distance

[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.

centerMethod

[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

startingCond

[character]: specifies the starting condition. Should be one of "randomAll", "randomK", "maxDist", "kmeans++", "kmeans+", "kmeans-" or "kmeans--" (see initialize

nbCriterion

[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).

scale

[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

Value

• An object ParKml.

Details

parKml3d is a constructor of object ParKml that provide adequate default value for the use of function kml3d.

Examples

### Generation of some data
cld1 <- generateArtificialLongData3d(c(15,15,15))

### Setting two different set of option :
(option1 <- parKml3d())
(option2 <- parKml3d(centerMethod=function(x)median(x,na.rm=TRUE)))

### Running kml. Formaly, the second exemple is 'k-median'
kml3d(cld1,4,1,toPlot="both",parAlgo=option1)
kml3d(cld1,4,1,toPlot="both",parAlgo=option2)