standardDeviation: Calculates decision weights using the standard deviation...

In avilesd/productConfig: Tools to analyze behavioral patterns from Product Configurators

Description

This function is used as the second step in weight.standard for calculating a decision weight for each attr in the decision matrix. The methodology of this method for determining the weights out of a decision matrix is given by references [1] and [2]. See References.

Usage

standardDeviation(aMatrix)

Arguments

normalizedMatrix

a numeric, normalized matrix. If indeed normalized it should only contain values between 0 and 1.

Details

The sum of the output of this functions should always equal 1.

Similar to entropy small differences between value attributes are rewarded a lower value and thus a relative lower weight.

Value

a weight vector(numeric vector with a sum of 1)

References

[1]Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: the CRITIC method. Computers & Operations Research, 22(7), 763-770.

[2]Jahan, A., & Edwards, K. L. (2013). Multi-criteria decision analysis for supporting the selection of engineering materials in product design. Butterworth-Heinemann.

Examples

#Runnable
standardDeviation(matrix(c(1.0, 0.85, 0.42, 0, 0.5, 0, 1, 0.7), 4, 2))
weights <- standardDeviation(matrix(c(1.0, 0.85, 0.42, 0, 0.5, 0, 1, 0.7), 2, 4))
sum(weights) should return 1

avilesd/productConfig documentation built on May 11, 2019, 4:08 p.m.