CPP.rh: CPP with multiple perspectives for human resources evaluation

In CPP: Composition of Probabilistic Preferences (CPP)

Description

This function computes the CPP-rh, using Beta PERT distributions to randomize the decision matrices. The CPP-rh is used to evaluate alternatives by integrating the CPP-Tri, the CPP-Malmquist, the CPP-Gini and the CPP by axes. The CPP-rh and the CPP-mb are very similar, but the CPP-rh does not include the alternatives's market value.

Usage

CPP.rh(t1, t2, q, s)

Arguments

t1	Decision matrix of Alternatives (rows) and Criteria (columns) in the previous moment '1'. Benefit criteria must be positive and cost criteria must be negative.
t2	Decision matrix of Alternatives (rows) and Criteria (columns) in the following moment '2'. Benefit criteria must be positive and cost criteria must be negative.
q	Vector of quantiles, indicating the classes' profiles.
s	Shape of a Beta PERT distribution, as described in the package 'mc2d'. There is no default value, however the higher the shape the higher the kurtosis, which emulates the precision of data.

Value

Class identifies the alternatives' classes, according to the selected profiles. CPP-RH returns the alternatives' scores per class.

Examples

## Decision matrix of the previous moment '1'.
Alt.1 = c(2,30,86,-5)
Alt.2 = c(4,26,77,-12)
Alt.3 = c(3,22,93,-4)
Alt.4 = c(6,34,65,-10)
Alt.5 = c(5,31,80,-8)
Alt.6 = c(6,29,79,-9)
Alt.7 = c(8,37,55,-15)
Alt.8 = c(10,21,69,-11)
t1 = rbind(Alt.1,Alt.2,Alt.3,Alt.4,Alt.5,Alt.6,Alt.7,Alt.8)
## Decision matrix of the following moment '2'.
Alt.1 = c(3,29,82,-3)
Alt.2 = c(6,28,70,-8)
Alt.3 = c(2,20,99,-8)
Alt.4 = c(5,31,62,-14)
Alt.5 = c(9,27,73,-5)
Alt.6 = c(4,33,85,-13)
Alt.7 = c(9,39,59,-10)
Alt.8 = c(8,19,77,-9)
t2 = rbind(Alt.1,Alt.2,Alt.3,Alt.4,Alt.5,Alt.6,Alt.7,Alt.8)
q = c(0.65,0.35) # quantiles of class profiles
s = 4 # Shape
CPP.rh(t1,t2,q,s)

CPP documentation built on May 2, 2019, 1:34 p.m.