kregcurves: k-groups of multiple regression curves

In clustcurv: Determining Groups in Multiples 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.

Author(s)

Nora M. Villanueva and Marta Sestelo.

Examples

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)

clustcurv documentation built on Jan. 14, 2021, 5:32 a.m.