clustcurv (version 2.0.1)

kregcurves: k-groups of multiple regression curves

Description

Function for grouping regression curves, given a number k, based on the k-means or k-medians algorithm.

Usage

kregcurves(y, x, z, k, kbin = 50, h = -1, algorithm = "kmeans", seed = NULL)

Arguments

y

Response variable.

x

Dependent variable.

z

Categorical variable indicating the population to which the observations belongs.

k

An integer specifying the number of groups of curves to be performed.

kbin

Size of the grid over which the survival functions are to be estimated.

h

The kernel bandwidth smoothing parameter.

algorithm

A character string specifying which clustering algorithm is used, i.e., k-means("kmeans") or k-medians ("kmedians").

seed

Seed to be used in the procedure.

Value

A list containing the following items:

measure

Value of the test statistic.

levels

Original levels of the variable fac.

cluster

A vector of integers (from 1:k) indicating the cluster to which each curve is allocated.

centers

An object containing the fitted centroids (mean of the curves pertaining to the same group).

curves

An object containing the fitted regression curves for each population.

Examples

# NOT RUN {
library(clustcurv)

# Regression: 2 groups k-means
r2 <- kregcurves(y = barnacle5$DW, x = barnacle5$RC,
z = barnacle5$F, k = 2, algorithm = "kmeans")

data.frame(level = r2$level, cluster = r2$cluster)



# }