| Type: | Package |
| Title: | Preference Selection Index Method (PSIM) |
| Version: | 0.1.0 |
| Maintainer: | Luana Oliveira <luana.azevedo.oliveira.2022@gmail.com> |
| Description: | The Preference Selection Index Method was created in (2010) and provides an innovative approach to determining the relative importance of criteria without pairwise comparisons, unlike the Analytic Hierarchy Process. The Preference Selection Index Method uses statistical methods to calculate the criteria weights and reflects their relative importance in the final decision-making process, offering an objective and non-subjective solution. This method is beneficial in multi-criteria decision analysis. The 'PSIM' package provides a practical and accessible tool for implementing the Preference Selection Index Method in R. It calculates the weights of criteria and makes the method available to researchers, analysts, and professionals without the need to develop complex calculations manually. More details about the Preference Selection Index Method can be found in Maniya K. and Bhatt M. G.(2010) <doi:10.1016/j.matdes.2009.11.020>. |
| URL: | https://github.com/luana1909/PSIM |
| Imports: | dplyr, matrixStats, magrittr, tidyverse |
| Language: | en-US |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Suggests: | rmarkdown, spelling, testthat (≥ 3.0.0) |
| Config/testthat/edition: | 3 |
| NeedsCompilation: | no |
| Packaged: | 2024-09-18 19:13:42 UTC; Luana de Azevedo |
| Author: | Luana Oliveira [aut, cre],
Marcos Santos 
[ctb] |
| Repository: | CRAN |
| Date/Publication: | 2024-09-19 15:40:12 UTC |
Preference Selection Index Method PSI
Description
Implementation of An PREFERENCE SELECTION INDEX METHOD - PSI More information about the method at https://doi.org/10.1016/j.matdes.2009.11.020 More information about the implementation at https://github.com/luana1909/PSIM/blob/main/DESCRIPTION The goal is to determine the weights of criteria
Arguments
data |
A numeric data matrix, columns are the criteria, rows are the alternatives |
optimization |
A character vector with definition of minimization or maximization for each criterion, expected 'min' or 'max' only |
Value
dataframe with 3 columns: critério, phi_j and psi_j
Examples
optimizations <- c("min","min", "max", "max") #"min" and "max" should be all lowercase
decision_matrix <- data.frame(criterio1 = c(7000, 15000, 20000),
criterio2 = c(700, 800, 1000),
criterio3 = c(280, 300, 180),
criterio4 = c(120, 880, 1200))
result <- psicalc(decision_matrix, optimizations)