affectIndiv: ~ Functions: affectIndiv & affectIndivC ~

In kml: K-Means for Longitudinal Data

~ Functions: affectIndiv & affectIndivC ~

Description

Given some longitudinal data (trajectories) and k clusters' centers, affectIndiv and affectIndivC affect each individual to the cluster whose centre is the closest.

Usage

affectIndiv(traj, clustersCenter, distance = function(x,y){dist(rbind(x, y))})
affectIndivC(traj, clustersCenter)

Arguments

traj	[matrix(numeric)]: longitudinal data. Each line is an individual, each column is a time measurement.
clustersCenter	[matrix(numeric)]: clusters centre. Each line is a cluster center, each column is a time measurement.
distance	[numeric <- function(trajectory,trajectory)]: use to estimate the distance between an individual and a clusters center.

Details

Given a matrix of clusters center clustersCenter (each line is a cluster center), the function affectIndiv affect each individual of the matrix traj to the closest clusters (according to distance). affectIndivC does the same but assume that the distance is the Euclidean distance. affectIndivC is writen in C (and is therefor much faster).

affectIndiv used with calculTrajMean simulates one k-means step.

Value

Object of classPartition.

Examples

#######################
### affectIndiv

### Some trajectories
traj <- gald()["traj"]

### 4 clusters centers
center <- traj[runif(4,1,nrow(traj)),]

### Affectation of each individual
system.time(part <- affectIndiv(traj,center))
system.time(part <- affectIndivC(traj,center))

kml documentation built on Oct. 30, 2024, 9:09 a.m.