kml (version 0.9.2)

generateArtificialLongData: ~ Function: generateArtificialLongData (or gald) ~

Description

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

Usage

gald(name="",clusterNames="",nbEachClusters=50,
    functionClusters=list(function(t){0},function(t){t},function(t){10-t},function(t){-0.4*t^2+4*t}),
    functionNoise=function(t,sdSeq){rnorm(1,0,3)},
    time=0:10,decimal=2,percentOfMissing=0)


generateArtificialLongData(name="",clusterNames="",nbEachClusters=50,
    functionClusters=list(function(t){0},function(t){t},function(t){10-t},function(t){-0.4*t^2+4*t}),
    functionNoise=function(t,sdSeq){rnorm(1,0,3)},
    time=0:10,decimal=2,percentOfMissing=0)

Arguments

name

[character]: name of the data set.

clusterNames

[vector(character)]: name of each clusters.

nbEachClusters

[vector(numeric)]: number of trajectories that each cluster must contain. If a single number is given, it is duplicated for all groups (see detail).

functionClusters

[list(function)]: lists the functions defining the average trajectories of each cluster. If a single function is given, it is duplicated for all groups (see detail).

functionNoise

[list(function)]: lists the functions generating the noise of each trajectory within its own cluster. If a single function is given, it is duplicated for all groups (see detail).

time

[vector(numeric)]: time at which measures are made.

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 duplicated for all groups (see detail).

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 Contact author:

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 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. Note that the number of cluster is define as the biggest length of variables nbEachClusters, functionCluters, functionNoise and percentOfMissing. So at least one of these four variables should be define for each clusters.

References

Article submited Web site: http://christophe.genolini.free.fr/kml

See Also

Overview: kml-package Classes: ArtificialLongData Methods: kml, choice Plot: plot(ClusterizLongData), plotSubGroups(ClusterizLongData), plotAll(ClusterizLongData)

Examples

par(ask=TRUE)

### Default example
ex1 <- generateArtificialLongData()
ex1
plot(ex1,colorTraj="black",colorMean="no")
plot(ex1)

### Three diverging lines
ex2 <- generateArtificialLongData(functionClusters=list(function(t)0,function(t)-t,function(t)t))
ex2
plot(ex2,colorTraj="black",colorMean="no")
plot(ex2)

### Three diverging lines with high variance, unbalance groups and missing value
ex3 <- generateArtificialLongData(
   functionClusters=list(function(t)0,function(t)-t,function(t)t),
   nbEachClusters=c(40,20,10),
   functionNoise=function(t){rnorm(1,0,3)},
   percentOfMissing=c(0.25,0.5,0.25)
)
ex3
plot(ex3,colorTraj="black",colorMean="no")
plot(ex3)

### Four strange functions
ex4 <- generateArtificialLongData(
    name="Four strange functions",
    clusterNames=c("Line","Poly2","Normal","Sinus"),
    nbEachClusters=c(100,300,200,100),
    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(1,0,5)},
    time=0:10,decimal=2,percentOfMissing=0.3)
ex4
plot(ex4,colorTraj="black",colorMean="no")
plot(ex4)

### To get only trajectories (if you want some artificial trajectories
###    to deal with another algorithm), use the getteur ["traj"]
ex5 <- gald(nbEachCluster=3,time=1:3)
ex5["traj"]

par(ask=FALSE)