rating: rating

In Prize: Prize: an R package for prioritization estimation based on analytic hierarchy process

Description

Estimates idealised priorities of alternatives (the rating AHP model).

Usage

rating(scale, alternative, NA_category = NULL, simulation = 500)

Arguments

scale	a pairwise comparison matrix (PCM) of rating categories.
alternative	a N by 2 character matrix, where N is the number of alternatives. The matrix includes alternatives on column #1 and the rating category they belong to on column #2.
NA_category	a character string or vector which specifies categories with the value of zero. Since zero is not achievable by PCM matrix.
simulation	simulation size for computation of Saaty's inconsistency

Value

An S4 object including the raw and normalized ahp priorities, Satty's inconsistency, and rating matrix.

Author(s)

Daryanaz Dargahi

References

T.L. Saaty. Rank from comparisons and from ratings in the analytic hierarchy/network processes. European Journal of Operational Research, 168(2):557-570, January 2006.

T.L. Saaty. The Analytic Hierarchy Process, Planning, Piority Setting, Resource Allocation. McGraw-Hill, New york, 1980.

Examples

mat <- matrix(nrow = 4, ncol = 4, data = NA)

# The category PCM matrix
rownames(mat) <- c('excellent','good','fair','poor')
colnames(mat) <- c('excellent','good','fair','poor')
mat[1,] <- c(1,2,4,6)
mat[2,] <- c(NA,1,2,4)
mat[3,] <- c(NA,NA,1,2)
mat[4,] <- c(NA,NA,NA,1)

# The alternative matrix
alt <- matrix(nrow = 5, ncol = 2, data = NA)
alt[,1] <- c("Andy", "Emily", "Nina", "Alex", "Jack")
alt[,2] <- c("good", "poor", "good", "fair", "excellent")

result <- rating(mat, alt, simulation = 500)

# Specifying a category with value of zero
alt <- rbind(alt, c('shannon', 'Not_available'))

result <- rating(mat, alt, NA_category = 'Not_available', simulation = 500)

Prize documentation built on April 28, 2020, 7:48 p.m.