# 1 Accumarray Examples

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## 1.1 Accumarry Basic Example

There are three unique values in ar_a, sum up the probabilities for each of the unique states. This is equivalent to sorting a matrix with a and prob, and computing sum for each.

ar_a = [3,2,1,3]';
ar_prob = [0.1,0.2,0.31,0.39]';
ar_sumprob = accumarray(ar_a, ar_prob);
tb_summed_prob = table(sort(unique(ar_a)), ar_sumprob);
disp(tb_summed_prob);

Var1    ar_sumprob
____    __________

1         0.31
2          0.2
3         0.49   

## 1.2 Accumarry For Discrete Random Variable

Upon solving a model, if we look for the mass at certain choices or states, accumarray could help aggregate up probabilities

a1 = [1,1,2,2]

a1 = 1x4
1     1     2     2

a2 = [3,2,1,3]

a2 = 1x4
3     2     1     3

a3 = [1,2,3,3]

a3 = 1x4
1     2     3     3

a = [a1;a2;a3]'/2

a = 4x3
0.5000    1.5000    0.5000
0.5000    1.0000    1.0000
1.0000    0.5000    1.5000
1.0000    1.5000    1.5000

prob_a = zeros(size(a)) + 1/12

prob_a = 4x3
0.0833    0.0833    0.0833
0.0833    0.0833    0.0833
0.0833    0.0833    0.0833
0.0833    0.0833    0.0833

[ar_idx_full, ~, ar_idx_of_unique] = unique(a)

ar_idx_full = 3x1
0.5000
1.0000
1.5000

ar_idx_of_unique = 12x1
1
1
2
2
3
2
1
3
1
2

mt_idx_of_unique = reshape(ar_idx_of_unique, size(a))

mt_idx_of_unique = 4x3
1     3     1
1     2     2
2     1     3
2     3     3

accumarray(mt_idx_of_unique(:,1), prob_a(:,1))

ans = 2x1
0.1667
0.1667

accumarray(mt_idx_of_unique(:,2), prob_a(:,2))

ans = 3x1
0.0833
0.0833
0.1667

accumarray(mt_idx_of_unique(:,3), prob_a(:,3))

ans = 3x1
0.0833
0.0833
0.1667