boot_clv {ClustVarLV}

Boostrapping for assessing the stability of a CLV result

Description

Bootstrapping on the individuals (in row) or the variables (in column) is performed. Choose the "row" option (the default), if the variables are measured on a random sample of individuals, Choose the "column" option, if the variables are taken from a population of variables. The first case is the more usual, but the second may occur, e.g. when variables are consumers assessing specific products. Each boostrapped data matrix is submitted to CLV in order to get partitions from 1 to nmax clusters. For each number of clusters, K, the Rand Index, the adjusted Rand Index, as well as the cohesion and the isolation of the clusters of the observed partition and the bootstrapped partitions are computed. These criteria are used for assessing the stability of the solution into K clusters. Parallel computing is performed for time saving.

Usage

boot_clv(object, case = "row", B = 100, nmax = NULL)

Arguments

object

: result of CLV()

case

: "row" or "column" corresponding to the random effect of the design

B

: the number of bootstrap to be run (100 by default)

nmax

: maximal size of the partitions to be considered (if NULL, the value of nmax used for the object is used)

Value

res

a list of length 4 for the Rand Index, Adjusted Rand Index, Cohesion and Isolation of the partition
results (matrix of size (B x nmax), respectively.

See Also

CLV