kml (version 0.9.0)

generateArtificialLongData: ~ function: generateArtificialLongData ~

Description

This function is used to builp up artificial data set of longitudinal data.

Usage

gald(name = "", clusterNames = "", nbEachClusters = rep(50, 3),
    functionClusters = list(function(t){t}, function(t){0},function(t){-t}),
    functionNoise = function(t){rnorm(1, 0, 0.1)},
    time = 0:7, decimal = 2, percentOfMissing = 0)


generateArtificialLongData(name = "", clusterNames = "", nbEachClusters = rep(50, 3),
    functionClusters = list(function(t){t}, function(t){0},function(t){-t}),
    functionNoise = function(t){rnorm(1, 0, 0.1)},
    time = 0:7, decimal = 2, percentOfMissing = 0)

Arguments

name

[character]: name of the data set.

clusterNames

[character]: name of each clusters.

nbEachClusters

[numeric]: number of trajectories that each cluster must contain. Note that the number of elements in nbEachClusters (the length of nbEachClusters) is used as a definition of the number of groups.

time

[numeric]: time at which measures are made.

functionClusters

[list(function)]: lists the functions generating the average trajectories of each cluster. If a single function is given, it is used for all groups. If several functions are given, the number of functions must correspond to the number of gr

functionNoise

[list(function)]: list of functions generating the noise of each trajectory within its own cluster. If a single function is given, it is used for all groups. If several functions are given, the number of functions must correspond to the num

decimal

[numeric]: number of decimals used to round up values.

percentOfMissing

[numeric]: percentage (between 0 and 1) of missing data generated in each cluster. If a single value is given, it is used for all groups. If several value are given, the number of values must correspond to the number of groups.

Value

• An object of class ArtificialLongData.

Author(s)

Christophe Genolini PSIGIAM: Paris Sud Innovation Group in Adolescent Mental Health INSERM U669 / Maison de Solenn / Paris Responsable :

English translation

Rapha�l Ricaud Laboratoire "Sport & Culture" / "Sports & Culture" Laboratory University of Paris 10 / Nanterre

Details

generateArtificialLongData (gald in short) is a function that enables the user to contruct artificial trajectories. Each individual is considered as belonging to a group. This group follows a certain theoretical trajectory, function of time. These functions (one per group) are given via the argument functionClusters. Within a group, the individual undergoes individal variations. Individual variations are given via the argument functionNoise. The number of individuals in each group is given by nbEachClusters. Finally, it is possible to add missing values randomly striking the data thanks to percentOfMissing.

See Also

kml-package,link{ArtificialLongData}

Examples

### Three diverging lines
ex1 <- generateArtificialLongData()
ex1
#plot(ex1)

### Three diverging lines with high variance
ex2 <- generateArtificialLongData(functionNoise=function(t){rnorm(1,0,3)})
ex2
#plot(ex2)

### Three diverging lines with unbalance groups
ex3 <- generateArtificialLongData(nbEachClusters=c(120,10,40))
ex3
#plot(ex3)

### Three diverging lines with missing data
ex4 <- generateArtificialLongData(percentOfMissing=c(0.5,0,0.25))
ex4
#plot(ex4)

### Four strange functions
ex5 <- generateArtificialLongData(
    name="Four strange functions",
    clusterNames=c("Line","Poly2","Normal","Sinus"),
    nbEachClusters=rep(100,4),
    functionClusters=list(function(t){-10+2*t},function(t){-0.6*t^2+6*t-7.5},function(t){10*sin(t)},function(t){30*dnorm(t,2,1.5)}),
    functionNoise=function(t){rnorm(1,0,4)},
    time=0:10,decimal=2,percentOfMissing=0.3)
ex5
#plot(ex5)


### Here is a data set. Our objectif is to find some clusters...
#layout(1)
#plot(ex5,color=c("black","no","no"))