sortandcut: Sort-and-Cut Reordering

In extracat: Categorical Data Analysis and Visualization

Description

An implementation of the sort-and-cut algorithm which is a mixture of the top-down-partitioning algorithm used by cfluctile and the reordering techniques available through optile. See details.

Usage

sortandcut(x,iter=20, tau0 = NULL, fun = "BCC", method = "WBCI")

Arguments

x	A matrix or 2D table.
iter	The number of random initial orderings for optile.
tau0	The minimum criterion value for a new cut. See cfluctile.
fun	The reordering function used by optile. Currently "BCC", "barysort" and "preclass" are available.
method	The method argument for cfluctile which defines the criterion used to find an optimal partition.

Details

The algorithm sorts a matrix using optile and cuts the reordered matrix once using cfluctile with nsplit = 1. Then the same procedure is applied to the resulting submatrices at the top left and the bottom right. The partitioning stops when the best cut leads to a criterion below tau0.

Value

The reordered matrix. The row and column order vectors are attached as an attributes attr(x ,"orders").

See Also

cfluctile

Examples

M <- arsim(12000,c(30,40),7,noise=0.3)
c1 <- cfluctile(M1<-optile(M, iter = 20))
c2 <- cfluctile(M2<-sortandcut(M))

extracat documentation built on July 17, 2018, 5:05 p.m.