binner {AssocBin}

Many split recursive binning

Description

'binner' is an iterative implementation of a recursive binary partitioning algorithm which accepts the splitting and stopping functions that guide partitioning as arguments.

Usage

binner(x, y, stopper, splitter, init = halfSplit, dropPoints = FALSE)

Arguments

x

numeric vector of the first variable to be binned

y

numeric vector of the second variable to be binned

stopper

function which accepts a list with elements 'x', 'y', 'bnds', 'expn', and 'n' and returns a logical indicating whether a split should occur for the bin defined by that list

splitter

function which accepts a list of lists with elements 'x', 'y', 'bnds', 'expn', and 'n' and returns a list where each element is a list of two corresponding to a split of the bin at that position in the original list

init

function like 'splitter' applied to the first bin

dropPoints

logical; should points be dropped from final bins?

Details

'binner' creates a two-dimensional histogram of the sample space of 'x' and 'y' by recursively splitting partitions of the data using 'splitter' until 'stopper' indicates that all partitions are not to be split. An optional argument 'init' gives the function applied to the first bin containing all points to initialize the binning algorithm.

Value

A list of lists each with elements 'x', 'y', 'bnds', 'expn', 'n', and 'stopped'.

Author(s)

Chris Salahub

Examples

## necessary set up
crits <- makeCriteria(depth >= 4, n < 10, expn <= 5)
stopFn <- function(bns) stopper(bns, crits)
spltFn <- function(bn) maxScoreSplit(bn, chiScores)
## generate data
x <- sample(1:100)
y <- sample(1:100)
## run binner
bins <- binner(x, y, stopper = stopFn, splitter = spltFn)