MAUT: MAUT

In conradbm/madmR: Multi-Attribute Decision Making for R

Description

This function allows you to import a csv into the correct data.matrix format for the madm package

Usage

MAUT(data = DM, algParams = c(), scales = c(), verbose = FALSE)

Arguments

data,	dataframe in read.data.matrix format
algParams,	default to c(), when the sensitivity function calls this function the user can pass specific algorithm parameters. These have a sanitiy check and then append in the correct parameter if correctly supplied.
scales,	default to c(), if scales supplied and supplied correctly, each attribute will get the appropriate scaling measure (linear, exponential, or logarithmic). Defaults to all linear scales if none supplied.
verbose,	echos print statements to understand input/output relation.

Details

1. https://github.com/conradbm/madm/blob/master/Examples/MAUT.xls

2. https://github.com/conradbm/madm/blob/master/Examples/SAW_and_Topsis.xls

Standard Decision Matrix Format (N+1)xD:

attribute1 attribute2 ... attributei ... attributeD weight alternative1 alternative2 . . . alternativeN

Value

list

Author(s)

Blake Conrad [e-mail]

Examples

data(maut_dm)
#no scales specified
maut_results <- MAUT(maut_dm) 
# all scales specified
maut_results2 <- MAUT(maut_dm, scales=c("linear", "exponential", "logarithmic"))
# some scales specified, all others default to linear. 
maut_results3 <- MAUT(maut_dm, scales=c("exponential", "", "logarithmic")) 

conradbm/madmR documentation built on May 28, 2019, 4:35 p.m.