DecisionAnalysis (version 1.1.0)

sensitivity_plot: Sensitivity Analysis Graph

Description

Takes a matrix of Single Attribute Value Function (SAVF) scores and shows how each alternative's MAVF scores change as the weight for that criteria changes from zero to one. The vertical black line represents the current weight.

Usage

sensitivity_plot(SAVF_matrix, weights, names, criteria, title = TRUE)

Arguments

SAVF_matrix

Matrix of SAVF scores

weights

Numeric vector of SAVF weights

names

The names of the alternatives

criteria

Numeric value equal to the column number of the SAVF_matrix that contains the desired criteria to conduct sensitivity analysis on

title

True=The title is the column name associated with the selected criteria, False=no title, Default: TRUE

Value

Sensitivity Analysis graph

Examples

# NOT RUN {
library(dplyr)

qbdata <- NFLcombine %>%
 filter(year == '2011', position == 'QB', wonderlic != '0') %>%
 select(c(2, 8, 9, 12, 15, 17, 18, 25, 20))  
qbdata[qbdata == 0] = NA

Height <- SAVF_exp_score(qbdata$heightinchestotal, 68, 75.21, 82)
Weight <- SAVF_exp_score(qbdata$weight, 185, 224.34, 275)
Forty <- SAVF_exp_score(qbdata$fortyyd, 4.3, 4.81, 5.4, increasing=FALSE)
Shuttle <- SAVF_exp_score(qbdata$twentyss, 3.8, 4.3, 4.9, increasing=FALSE)
Vertical <- SAVF_exp_score(qbdata$vertical, 21, 32.04, 40)
Broad <- SAVF_exp_score(qbdata$broad, 90, 111.24, 130)
Wonderlic <- SAVF_exp_score(qbdata$wonderlic, 0, 27.08, 50)

SAVF_matrix = cbind(Height, Weight, Forty, Shuttle, Vertical, Broad, Wonderlic)
weights = c(0.096, 0.224, 0.092, 0.138, 0.152, 0.228, 0.07)

sensitivity_plot(SAVF_matrix, weights, qbdata$name, 4)

# }