pvclust_prep: A MVDA Function

Description Usage Arguments Value

Description

This function calculate clustering of single view patient prototypes by using pvclust packages.

Usage

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pvclust_prep(DB, hclust.method = "ward", nboot = 100,
  dist.method = "correlation", alpha = 0.95, show.print = F, r = 1,
  printLocation = ".", km_center = F, nCenters)

Arguments

DB

is your matrix dataset

hclust.method

is the the agglomeration method to be used for the hclust function. Default value is "ward".

nboot

is the number of bootstrap replications. The default is 100.

dist.method

is the distance measure to be used.

r

is numeric vector which specifies the relative sample sizes of bootstrap replications. The default is 1.

nCenters

is the desidered number of cluster

nCenters

is the desidered number of clusters

Value

a list containing three field: pvclust.res is the pvclust clustering results. clustering is the vector with clustering assignment. center is the matrix with center prototypes.


angy89/MVDA_package documentation built on May 7, 2019, 8:58 p.m.