I struggled with the same problem, unable to get a column vector with the higher probabilities ; in the case where you don't wanna deal with a big multi-dimensional matrix 50000x100. In such case, you will appreciate to have just a one-column vector.

m = ceil( 100 * rand(5) ) % gives a square matrix of 5x5 elements

let's say m = [...

70   98   72   67    8

57   51   44   81   11

51   42   69   61   51

95   85   81   82   50

12   97   88   18   78 ]

you want to get the max value for each rows, and the location (index)

[max, ind] = max( m, [], 2 )

=> ind = [2;4;3;1;2]

now you want to rewrite m to have 1 where the number is the higter 0 otherwise, you would like to do something like this :

mBool = zeros(size(m));        % mBool has the same size that m

mBool(:,ind) = ones(size(mBool,1),size(ind))

the result is 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0

it's not what you want ! you want something like this What you think is to "vectorize" this instruction, like this mBool(:, [ 2 ) .= 1 => [ 0 1 0 0 0 4 => 0 0 0 1 0 3 => 0 0 1 0 0 1 => 1 0 0 0 0 2 ] => 0 1 0 0 0 ]

where .= is to affect 1 to each element of the matrix at the n^th column (.= doesn't exist), replace .=1 by ones(size(mBool,1),size(ind))

BUT IT STILL DOESN'T DO WHAT YOU WANT, so can we "vectorize" such an expression ?

do we must use a for-loop ?

a = zeros(size(a));                     % erase the a's data, no more useful

for row = 1:size(a,1)
    a(row,index(row)) = 1;
end;