Compute the perimeter density matrix Introduction

The perimeter density matrix is an infinite binary matrix M defined as follows.
Consider a (1-based) index (x, y), and denote by M[x, y] the rectangular sub-matrix spanned by the corner (1, 1) and (x, y).
Suppose that all values of M[x, y] except Mx, y, the value at index (x, y), have already been determined.
Then the value Mx, y is whichever of 0 or 1 that puts the average value of M[x, y] closer to 1 / (x + y).
In case of a tie, choose Mx, y = 1.

This is the sub-matrix M[20, 20] with zeros replaced by dots for clarity:

1 . . . . . . . . . . . . . . . . . . .
. . . . . 1 . . . . . . . . . . . . . .
. . 1 . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . 1 . . . . . . . . . . . . . . .
. 1 . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 1 . .
. . . . . . . . . . . . . . 1 . . . . .
. . . . . . . . . . . . 1 . . . . . . .
. . . . . . . . . . 1 . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . . . 1 . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . . 1 . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . 1 . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . .


For example, we have M1, 1 = 1 at the upper left corner, since 1 / (1 + 1) = &half;, and the average of the 1 &times; 1 sub-matrix M[1, 1] is either 0 or 1; that's a tie, so we choose 1.

Consider then the position (3, 4).
We have 1 / (3 + 4) = 1/7, and the average of the sub-matrix M[3, 4] is 1/6 if we choose 0, and 3/12 if we choose 1.
The former is closer to 1/7, so we choose M3, 4 = 0.

Here is the sub-matrix M[800, 800] as an image, showing some of its intricate structure.

The task

Given a positive integer N &lt; 1000, output the N &times; N sub-matrix M[N, N], in any reasonable format.
The lowest byte count wins.
R, 158 154 141  bytes
Edit: Because the only 1 in the upper 2x2 submatrix is the top left M[1,1] we can start the search for 1s when {x,y}&gt;1 so no need for the if statement.
M=matrix(0,n&lt;-scan(),n);M[1]=1;for(i in 2:n)for(j in 2:n){y=x=M[1:i,1:j];x[i,j]=0;y[i,j]=1;d=1/(i+j);M[i,j]=abs(d-mean(x))&gt;=abs(d-mean(y))};M

The solution is highly inefficient as the matrix is duplicated twice for each iteration. n=1000 took just under two and a half hours to run and produces a matrix of 7.6 Mb.
Ungolfed and explained
M=matrix(0,n&lt;-scan(),n);                        # Read input from stdin and initialize matrix with 0s
M[1]=1;                                         # Set top left element to 1
for(i in 2:n){                                  # For each row    
    for(j in 2:n){                              # For each column
        y=x=M[1:i,1:j];                         # Generate two copies of M with i rows and j columns
        x[i,j]=0;                               # Set bottom right element to 0
        y[i,j]=1;                               # Set bottom right element to 1
        d=1/(i+j);                              # Calculate inverse of sum of indices
        M[i,j]=abs(d-mean(x))&gt;=abs(d-mean(y))   # Returns FALSE if mean(x) is closer to d and TRUE if mean(y) is
    }
};
M                                               # Print to stdout

Output for n=20
      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20]
[1,]     1    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[2,]     0    0    0    0    0    1    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[3,]     0    0    1    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[4,]     0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[5,]     0    0    0    0    1    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[6,]     0    1    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[7,]     0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[8,]     0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     1     0     0
[9,]     0    0    0    0    0    0    0    0    0     0     0     0     0     0     1     0     0     0     0     0
[10,]    0    0    0    0    0    0    0    0    0     0     0     0     1     0     0     0     0     0     0     0
[11,]    0    0    0    0    0    0    0    0    0     0     1     0     0     0     0     0     0     0     0     0
[12,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[13,]    0    0    0    0    0    0    0    0    0     1     0     0     0     0     0     0     0     0     0     0
[14,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[15,]    0    0    0    0    0    0    0    0    1     0     0     0     0     0     0     0     0     0     0     0
[16,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[17,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[18,]    0    0    0    0    0    0    0    1    0     0     0     0     0     0     0     0     0     0     0     0
[19,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0
[20,]    0    0    0    0    0    0    0    0    0     0     0     0     0     0     0     0     0     0     0     0