Ajustes

DESCRIPTION

@@ -2,13 +2,13 @@ Package: PrometheeTools
 Title: PROMETHEE and GLNF for Ranking and Sorting Problems
 Version: 0.0.0.9000
 Authors@R: c( 
-    person("Felipe", "Barrera", , "ifelipebj@hotmail.com", role = c("aut", "cre"),
+    person("Felipe", "Barrera", , "ifelipebj@hotmail.com", role = c("aut", "cre", "cph"),
            comment = c(ORCID = "0000-0003-3236-6966")),
     person("Marina", "Segura", , "marina.segura@ucm.es", role = "aut",
            comment = c(ORCID = "0000-0002-6068-960X")),
     person("Concepcion", "Maroto", , "cmaroto@eio.upv.es", role = "aut",
            comment = c(ORCID = "0000-0001-8512-3197")))
-Description: Functions based on PROMETHEE (Preference Ranking Organisation METHod for Enrichment of Evaluations), a multicriteria decision-making method,to evaluate a large number of alternatives to obtain partial and complete rankings. Moreover, the package provides the GLNF (Global Local Net Flow) sorting algorithm to classify alternatives into ordered categories and quality index function to mesure the classification quality.
+Description: Multicriteria decision-making evaluations based on PROMETHEE (Preference Ranking Organisation METHod for Enrichment of Evaluations) method,to assess a large number of alternatives to obtain partial and complete rankings. Moreover, the package provides the GLNF (Global Local Net Flow) sorting algorithm to classify alternatives into ordered categories and quality index function to mesure the classification quality.
 License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

R/GLNF.R

@@ -52,9 +52,6 @@
 #' - In the objective write "max" to maximize or "min" to minimize.
 #' - The sum of the weights of all criteria must be equal to 1.
 #' @examples
-#'# The evaluation matrix is defined to classify 30 customers in four categories
-#'# according to five criteria. Five limiting profiles (r1,r2,r3,r4,r5) are
-#'# included in the rows as alternatives.
 #'matrix_evaluation <- data.frame (
 #'
 #'Alternative = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
@@ -81,8 +78,6 @@
 #'           3, 3, 1, 1, 2, 5, 4, 2, 2, 5,
 #'           4, 5, 1, 4, 2, 1, 5, 1, 1, 2,
 #'           5, 4, 3, 2, 1))
-#'
-#'# The matrix with the criteria parameters is defined
 #'data_criteria <- data.frame(
 #'Parameter = c("Function Type", "Indifference Threshold",
 #'              "Preference Threshold","Objetive", "Weight"),
@@ -91,15 +86,9 @@
 #'Recency = c("usual", 0.00, 0.00, "min", 0.1),
 #'Financial_score = c("linear", 0.00, 10, "max", 0.2),
 #'Length = c("usual", 0.00, 0.00, "max", 0.1))
-#'
-#'###############################
 #'RS <- GLNF(matrix_evaluation, data_criteria)
-#'# Final classification of the 30 customers into four ordered groups
 #'RS$Class
-#'# It is possible to check the details of global and local searches.
-#'# Show global classification results
 #'RS$Global
-#'# Show local classification results
 #'RS$Local1
 #'RS$Local2
 GLNF <- function(matrix_evaluation, data_criteria) {

R/PROMETHEEII.R

@@ -36,8 +36,6 @@
 #' of alternatives (it has been tested with 10,000 alternatives) much higher
 #' than the previous implementations in R (`promethee123` and `PROMETHEE`).
 #' @examples
-#'# The evaluation matrix is defined to rank 30 customers according to five
-#'# criteria.
 #'matrix_evaluation <- data.frame (
 #'
 #'Alternative = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
@@ -58,8 +56,6 @@
 #'Length = c(4, 3, 3, 2, 2, 2, 2, 3, 2, 4,
 #'           3, 3, 1, 1, 2, 5, 4, 2, 2, 5,
 #'           4, 5, 1, 4, 2, 1, 5, 1, 1, 2))
-#'
-#'# The matrix with the criteria parameters is defined
 #'data_criteria <- data.frame(
 #'Parameter = c("Function Type", "Indifference Threshold",
 #'              "Preference Threshold","Objetive", "Weight"),
@@ -68,12 +64,8 @@
 #'Recency = c("usual", 0.00, 0.00, "min", 0.1),
 #'Financial_score = c("linear", 0.00, 10, "max", 0.2),
 #'Length = c("usual", 0.00, 0.00, "max", 0.1))
-#'
-#'###############################
 #'RS <- PROMETHEEII(matrix_evaluation, data_criteria)
-#'# Positive flows, negative flows and net flows
 #'RS$NF
-#'# Net flows by criteria
 #'RS$NFC
 PROMETHEEII <- function(matrix_evaluation, data_criteria) {
   # Identify columns of criteria and alternative column

R/SILS.R

@@ -46,13 +46,7 @@
 #' @importFrom ggplot2 ggplot aes geom_bar scale_fill_manual theme_minimal
 #' labs geom_hline scale_x_discrete scale_y_continuous theme element_text margin
 #' @examples
-#'# The number of categories or groups to be evaluated is defined.
-#'k <- 4
-#'
-#'# The evaluation matrix is defined to evaluate 30 clients who were classified
-#'# into four groups according to five criteria and five limiting profiles.
-#'# (r1,r2,r3,r4,r5). The last column contains the categories in numerical
-#'# format.
+#' k <- 4
 #' matrix_evaluation <- data.frame (
 #'
 #'Alternative = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10,
@@ -83,7 +77,6 @@
 #'               1, 4, 2, 2, 2, 2, 2, 1, 3, 4,
 #'               3, 3, 3, 2, 4, 2, 1, 4, 3, 4,
 #'               NA, NA, NA, NA, NA))
-#'# The matrix with the criteria parameters is defined
 #'data_criteria <- data.frame(
 #'  Parameter = c("Function Type", "Indifference Threshold",
 #'                "Preference Threshold","Objetive", "Weight"),
@@ -92,8 +85,6 @@
 #'  Recency = c("usual", 0.00, 0.00, "min", 0.1),
 #'  Financial_score = c("linear", 0.00, 10, "max", 0.2),
 #'  Length = c("usual", 0.00, 0.00, "max", 0.1))
-#'
-#'###############################
 #'RS <- SILS(matrix_evaluation, data_criteria, k, SILS_plot = TRUE)
 #'print(RS)
 SILS <- function(matrix_evaluation, data_criteria, k, SILS_plot = FALSE) {