Which.Max Ties Method in R

which.max ties method in R

You could do like this:

x<-c(1,2,1,4,3,4)
#identical to which.max, except returns all indices with max
which(x==max(x)) 
[1] 4 6
z<-which(x==max(x))
z[length(z)]
[1] 6
#or with tail
tail(which(x==max(x)),1)
[1] 6

edit:

Or, you could also use max.col function for vectors like this:

max.col(t(x),"last")
[1] 6
#or
max.col(matrix(x,nrow=1),"last")
[1] 6

edit: Some benchmarking:

x<-sample(1:1000,size=10000,replace=TRUE)
library(microbenchmark)
microbenchmark(which.max(x),{z<-which(x==max(x));z[length(z)]}, 
     tail(which(x==max(x)),1),max.col(matrix(x,nrow=1),"last"),
     max.col(t(x),"last"),which.max(rev(x)),times=1000)
Unit: microseconds
                                             expr     min      lq  median      uq       max neval
                                     which.max(x)  29.390  30.323  30.323  31.256 17550.276  1000
 {     z <- which(x == max(x))     z[length(z)] }  40.586  42.452  42.919  44.318   631.178  1000
                      tail(which(x == max(x)), 1)  57.380  60.646  61.579  64.844   596.657  1000
             max.col(matrix(x, nrow = 1), "last") 134.353 138.085 139.485 144.383   710.949  1000
                            max.col(t(x), "last") 116.159 119.425 121.291 125.956   729.610  1000
                                which.max(rev(x))  89.569  91.435  92.368  96.566   746.404  1000

So all methods seem to be slower than the original (which gives wrong result), but z <- which(x == max(x));z[length(z)] seems to be fastest option of these.

Are there ways to randomly sample among ties in the R function which.max()?

which(vec == max(vec)) will match all ties. You can then pick one at random using sample(which(vec == max(vec)), 1).

As you mentioned in the comments, sample does something annoying when the supplied vector is of length 1. So when there is only one maximum.

You can fix this as follows:

maxima <- which(vec == max(vec))
if(length(maxima) > 1){
  maxima <- sample(maxima, 1)
}

which.max() to extract the last largest value

names(rev(test))[apply(rev(test), 1, which.max)]
[1] "M.trust" "I.trust" "I.trust" "M.trust" "M.trust" "H.trust"

R - find out if a the column containing the max value of a row is tied with another column

An option would be to get the max and check the count of max elements by row

df$tie <- apply(df[1:5], 1, function(x) sum(x == max(x)) > 1)
df$tie
#[1] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE

---

Or using rowSums

rowSums(df[1:5] == do.call(pmax, df[1:5])) > 1
#[1] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE

NOTE: Both the methods are generalized and can take care of multiple conditions

Find all tied maximum values in a row and return true or false if column contains max value

A simple and efficient solution would be to get row-wise maximum using do.call and pmax and compare it with the dataframe to get logical vectors which can be assigned as new columns.

df[paste0(names(df), "max")] <- df == do.call(pmax, df)

df
#   v1 v2 v3 v4 v5 v1max v2max v3max v4max v5max
#1   0  2  4  0  0 FALSE FALSE  TRUE FALSE FALSE
#2   1  1  1  1  1  TRUE  TRUE  TRUE  TRUE  TRUE
#3   2  4  6  2  6 FALSE FALSE  TRUE FALSE  TRUE
#4   3  7  7  7  3 FALSE  TRUE  TRUE  TRUE FALSE
#5   4  6  8  4  6 FALSE FALSE  TRUE FALSE FALSE
#6   5  7  9  5  9 FALSE FALSE  TRUE FALSE  TRUE
#7   6  8  0  6  8 FALSE  TRUE FALSE FALSE  TRUE
#8   7  9  1  7  9 FALSE  TRUE FALSE FALSE  TRUE
#9   8  0  2  8  0  TRUE FALSE FALSE  TRUE FALSE
#10  9  1  3  9  1  TRUE FALSE FALSE  TRUE FALSE

---

A solution with apply could be

df[paste0(names(df), "max")] <- t(apply(df, 1, function(x) x == max(x)))

Handling ties in finding index of n th maximum value in R

library(data.table)

 DT<-structure(list(Refer_1 = c(11L, 15L, 7L, 19L, 104L, 24L, 11L, 
22L, 39L, 19L), Refer_2 = c(17L, 21L, 13L, 25L, 204L, 36L, 14L, 
25L, 45L, 37L)), .Names = c("Refer_1", "Refer_2"), row.names = c(NA, 
-10L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000000000130788>) 

DT[,lapply(.SD, order,decreasing=TRUE)]
    Refer_1 Refer_2
 1:       5       5
 2:       9       9
 3:       6      10
 4:       8       6
 5:       4       4
 6:      10       8
 7:       2       2
 8:       1       1
 9:       7       7
10:       3       3

Ties when finding minimum in R

just change which.min(df1[x,]) to which(df1[x,]==min(df1[x,])). You can even shorten your code by using apply instead of sapply

> apply(df1, 1, function(x) which(x==min(x)))
[[1]]
y 
2 

[[2]]
x 
1 

[[3]]
x y 
1 2 

---

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