| maxCol {base} | R Documentation |
Find the maximum position for each row of a matrix, breaking ties at random.
max.col(m, ties.method=c("random", "first", "last"))
m |
numerical matrix |
ties.method |
a character string specifying how “ties” are
handled, "random" by default; can be abbreviated; see
Details. |
When ties.method = "random", as per default, ties are broken at
random. In this case, the determination of “tie” assumes that
the entries are probabilities: there is a relative tolerance of
1e-5, relative to the largest entry in the row.
If ties.method = "first", max.col returns the
column number of the first of several maxima in every row, the
same as unname(apply(m, 1, which.max)).
Correspondingly, ties.method = "last" returns the last
of possibly several indices.
index of a maximal value for each row, an integer vector of
length nrow(m).
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. New York: Springer (4th ed).
which.max for vectors.
table(mc <- max.col(swiss))# mostly "1" and "5", 5 x "2" and once "4"
swiss[unique(print(mr <- max.col(t(swiss)))) , ] # 3 33 45 45 33 6
set.seed(1)# reproducible example:
(mm <- rbind(x = round(2*runif(12)),
y = round(5*runif(12)),
z = round(8*runif(12))))
## Not run:
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12]
x 1 1 1 2 0 2 2 1 1 0 0 0
y 3 2 4 2 4 5 2 4 5 1 3 1
z 2 3 0 3 7 3 4 5 4 1 7 5
## End(Not run)
## column indices of all row maxima :
str(lapply(1:3, function(i) which(mm[i,] == max(mm[i,]))))
max.col(mm) ; max.col(mm) # "random"
max.col(mm, "first")# -> 4 6 5
max.col(mm, "last") # -> 7 9 11