R: ~ Functions: calculTrajMean & calculTrajMeanC ~

calculTrajMean {kml} | R Documentation

## ~ Functions: calculTrajMean & calculTrajMeanC ~

### Description

Given some longitudinal data and a cluster affectation, `calculTrajMean` and `calculTrajMeanC` compute the mean trajectories of each cluster.

### Usage

    calculTrajMean(traj, clust, centerMethod = function(x){mean(x, na.rm =TRUE)})
    calculTrajMeanC(traj, clust)

### Arguments

`traj` | `[matrix(numeric)]`: longitudinal data. Each line is an individual, each column is a time measurement.
`clust` | `[vector(numeric)]`: affectation of each individual.
`centerMethod` | `[trajectory <- function(matrix(numeric))]`: function that compute the mean trajectory of a group of trajectories.

### Details

Given a vector of affectation to a cluster, the function `calculTrajMean` compute the "central" trajectory of each clusters. The "center" can be define using the argument `centerMethod`. `calculTrajMeanC` does the same but assume that the center definition is the classic "mean". `calculTrajMeanC` is writen in C (and is therefor much faster).

`affectIndiv` used with `calculTrajMean` simulates one k-means step.

### Value

A matrix with k line and t column containing k clusters centers. Each line is a center, each column is a time measurement.

### Examples

    #######################
    ### calculMean

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

    ### A cluster affectation
    clust <- initializePartition(3,200,"randomAll")

    ### Computation of the cluster's centers
    system.time(centers <- calculTrajMean(traj,clust))
    system.time(centers <- calculTrajMeanC(traj,clust))

[Package kml version 2.4.1 Index]