lminter: Interpolating Logical Matrices

In cba: Clustering for Business Analytics

Interpolating Logical Matrices

Description

Interpolate a logical matrix into a lower-resolution representation.

Usage

lminter(x, block.size = 1, nbin = 0)

Arguments

x	a logical matrix.
block.size	the interpolation block size.
nbin	the number of density bins.

Details

Partitions a binary matrix into square blocks of specified size (length) and interpolates the number of TRUE values per block using the specified number of bins.

Note that the effective number of bins is one greater than the specified number because the zero bin is always included. Excess rows and columns at the lower or right margins of the matrix are ignored.

If the number of bins is null counts are mapped to zero and one thresholding at half of the number of distinct count values including zero. Thus, for even numbered block sizes there is a bias towards zero.

Value

An integer matrix of bin numbers.

Note

Package internal function.

Author(s)

Christian Buchta

See Also

lmplot for plotting logical matrices.

Examples

## Not run: 
x <- matrix(sample(c(FALSE, TRUE), 4 ,rep=TRUE), ncol=2)
lminter(x, block.size=2, nbin=2)

## End(Not run)

cba documentation built on Dec. 7, 2022, 5:17 p.m.