ddgraph (version 1.16.0)

independent.contributions.formula: Generate class labels by independent contributions of two variables

Description

Generate class labels by using the readout mechanism. Logical formula is applied to two variables which are read out from the real data using the var1 and var2 probabilities. This only works with binary variables.

Usage

independent.contributions.formula(data, var1, var2, var1.prob1, var1.prob0, var2.prob1, var2.prob0, logical.formula, false.neg=0, false.pos=0)

Arguments

data

a matrix or data.frame containing binary observations (columns are variables)

var1

index or name of the first variable

var2

index or name of the second variable

var1.prob1

the conditional probability P(class labels = 1|var1=1)

var1.prob0

the conditional probability P(class labels = 1|var1=0)

var2.prob1

the conditional probability P(class labels = 1|var2=1)

var2.prob0

the conditional probability P(class labels = 1|var2=0)

logical.formula

logical formula to apply

false.neg

a false negative probability

false.pos

a false positive probability

Value

Examples

data <- cbind("a"=c(0,0,1,1), "b"=c(0,1,0,1))
independent.contributions.formula(data, "a", "b", 0.9, 0.1, 0.9, 0.1, "a | b")