binstatistics: Statistics for bins

In AssocBin: Measuring Association with Recursive Binning

Statistics for bins

Description

These functions compute statistics based on observed and expected counts for a list of bins.

Usage

binChi(bins, agg = sum)

binMI(bins, agg = sum)

binAbsDif(bins, agg = sum)

Arguments

bins	a list of bins, each a list with elements 'x', 'y', 'depth', 'bnds' (list with elements 'x' and 'y'), 'expn', 'n'
agg	function which is aggregates the individual statistics computed over each bin

Details

Binstatistics

Three functions are provided by default, 'binChi' computes the chi-squared statistic by taking the squared difference between observed and expected counts and dividing this by the expected counts. 'binMi' computes the mutual information for each bin using the observed and expected counts. Finally, 'binAbsDif' computes the absolute difference between observed and expected counts. Each function first computes a value on every bin independently and stores all these values in memory before using the function provided in the optional argument 'agg' to aggregate these values.

Value

A list with elements 'residuals', 'stat', and 'nbins' reporting the individual statistic values (possibly transformed), the aggegrated statistic value, and the number of bins in 'bins'

Functions

• binChi(): Chi-squared statistic

• binMI(): Mutual information

• binAbsDif(): Absolute difference between observed and expected

Author(s)

Chris Salahub

Examples

binList1 <- list(list(x = c(1,2), y = c(3,1), depth = 1, n = 2,
                      expn = 2),
                list(x = c(3,4), y = c(2,4), depth = 1, n = 2,
                     expn = 2))
binList2 <- list(list(x = c(1,2), y = c(3,1), depth = 6, n = 2,
                      expn = 4),
                list(x = c(), y = c(), depth = 1, n = 0, expn = 1))
binChi(binList1)
binChi(binList2)
binMI(binList1)
binMI(binList2)
binAbsDif(binList2)

AssocBin documentation built on April 3, 2025, 7:46 p.m.