Dinorms {lingua}R Documentation

Dinorms - Natural aggregation of dichotomic values

Description

Dinorms are functions for aggregation of dichotomic values from the [-1,1] interval. The values are assumed to be supports for two opposite situations. It can be e.g. reasons for cold vs. hot situations, or underexpressed vs. overexpressed genes as reasons for positive vs. negative advices for a treatment.

Usage

dinorms.thresholds(thresh = NULL)
dinorms.modes(modes = NULL)
dinorms.aggregate(vect)
dinorms.boost(vect, powers, count, limit = 0)

Arguments

thresh either none or vector of two [0,1] values for addition, combination thresholds
modes either none or name-pair for addition: one of "maximum", "coproduct", "summation", and combination: one of "maximum", "codivision", "subtraction", "stabilized" modes
vect [-1,1]-valued vector to aggregate
powers [0,1]-valued vector of data strengths
count number of resamples for the boosting
limit to use data with >= limit power

Details

The Dinorms aggregation is based on fuzzy logic connectives, separated into twofold process. First, negative and positive values are aggregated separately in the natural way. Then the result values are combined into a final aggregation (e.g. prognosis).

Value

thresholds and modes give the set option values, aggregate gives the sequence of negative, positive, and combined results, boost gives strengthen results, with desc being c(mean, variance).

Note

Look at the Bioplexity and Enduce webs for more information. http://www.bioplexity.org/analysis/ http://www.tangloid.net/enduce/

Author(s)

Martin Saturka

References

Bioplexity www.bioplexity.org

See Also

See Also lingua, contifiers, clustions

Examples

library(lingua)
## initial settings
dinorms.thresholds(c(0.1, 0.1))
dinorms.modes(c("cop", "sub"))
## aggregate some random vector
vect <- runif(20, -1, 1)
dinres <- dinorms.aggregate(vect)
## boosting the dinorms
powers <- runif(length(vect))
dinorms.boost(vect, powers, 10, 0.5)

[Package lingua version 1.0-1 Index]