I would like to create a column called Weight, which would be as follows:
Weight = Mode (constant * mean).
Mode is column of my database.
Constant is alternative/total alternatives, in this case will be 0,1, because 1/10.
Mean is the average of the values corresponding to a specific alternative. For example, the mean for alternative 10 is (3 2 2 3)/4 = 2,5.
Making an example for alternative 10 then. The weight would be 2 (0,1.2,5) = 2,25.
database<-structure(list(Alternatives = c(3, 4, 5, 6, 7, 8, 9, 10, 11,
12), Method1 = c(1L, 10L, 7L, 8L, 9L, 6L, 5L, 3L, 4L, 2L), Method2 = c(1L,
8L, 6L, 7L, 10L, 9L, 4L, 2L, 3L, 5L), Method3 = c(1L, 10L, 7L,
8L, 9L, 6L, 4L, 2L, 3L, 5L), Method4 = c(1L, 9L, 6L, 7L, 10L,
8L, 5L, 3L, 4L, 2L), Mode = c(1, 10, 6, 7, 9, 6, 4, 2, 3, 2)), class = "data.frame", row.names = c(NA,-10L))
Alternatives Method1 Method2 Method3 Method4 Mode
1 3 1 1 1 1 1
2 4 10 8 10 9 10
3 5 7 6 7 6 6
4 6 8 7 8 7 7
5 7 9 10 9 10 9
6 8 6 9 6 8 6
7 9 5 4 4 5 4
8 10 3 2 2 3 2
9 11 4 3 3 4 3
10 12 2 5 5 2 2
CodePudding user response：
If your constant equals 0.1 , then try
database |> mutate(Weight = Mode
.1 * ((Method1 Method2 Method3 Method4) / 4))
- Output
Alternatives Method1 Method2 Method3 Method4 Mode Weight
1 3 1 1 1 1 1 1.100
2 4 10 8 10 9 10 10.925
3 5 7 6 7 6 6 6.650
4 6 8 7 8 7 7 7.750
5 7 9 10 9 10 9 9.950
6 8 6 9 6 8 6 6.725
7 9 5 4 4 5 4 4.450
8 10 3 2 2 3 2 2.250
9 11 4 3 3 4 3 3.350
10 12 2 5 5 2 2 2.350
if it is the probability then change it to
database |> mutate(Weight = Mode
1/ nrow(database) * ((Method1 Method2 Method3 Method4) / 4)) |>
mutate(rank = rank(Weight))
CodePudding user response：
This can also be accomplished using the base package.
attach(database)
database$Weight = .1 * (Method1 Method2 Method3 Method4)/4 Mode
database
# Alternatives Method1 Method2 Method3 Method4 Mode Weight
#1 3 1 1 1 1 1 1.100
#2 4 10 8 10 9 10 10.925
#3 5 7 6 7 6 6 6.650
#4 6 8 7 8 7 7 7.750
#5 7 9 10 9 10 9 9.950
#6 8 6 9 6 8 6 6.725
#7 9 5 4 4 5 4 4.450
#8 10 3 2 2 3 2 2.250
#9 11 4 3 3 4 3 3.350
#10 12 2 5 5 2 2 2.350
One can also use the rank function on the resulting "weight" column.
database$weight = rank(database$weight)