Assign rank to values in a matrix

Hello, I have 10*10 matrix that I want to assign a rank to each element of the matrix in descending order from 1 to 100. I know how to assign in a rank in a specific row or column using for example tiedrank but I want to assign a ranking to the whole matrix in a way that I have a 10*10 matrix at the end that represents the rank at each element corrosponding to the value from 1 to 100. Can someone please help me? I'd appreicate it. Thank you in advance.

[MarshallSc]

No one has any opinion?

Answer 1

[the cyclist]

Here is one way. (I did a smaller array, so the result is easier to verify.)

% Set random seed for reproducibility
rng default

% Generate a random input
M = rand(3)

M = 3×3

0.8147 0.9134 0.2785 0.9058 0.6324 0.5469 0.1270 0.0975 0.9575

% Sort the elements
sorted = sort(M(:));

% Find the index from M to the sorted elements
[~,index] = ismember(M(:),sorted);

% Reshape to the original size
rankElements = reshape(index,size(M))

rankElements = 3×3

6 8 3 7 5 4 2 1 9

[MarshallSc]

Thanks alot, really appreciate it.

Answer 2

[Walter Roberson]

YourArray = randi(100, 10, 10)

YourArray = 10×10

46 59 74 56 32 30 26 19 87 36 10 28 60 62 92 2 26 36 93 70 81 5 33 52 64 19 60 32 72 60 67 45 26 31 44 37 43 61 26 96 34 28 11 75 29 87 90 19 61 64 32 13 68 87 97 68 48 69 87 10 71 15 75 11 15 8 11 46 57 62 69 13 58 1 63 17 13 53 41 87 23 28 79 41 48 72 9 53 81 44 94 2 92 34 56 67 56 5 1 9

[~, idx] = sort(YourArray(:), 'descend');
rank = zeros(size(YourArray));
rank(idx) = 1:numel(YourArray)

rank = 10×10

50 39 18 42 65 68 74 79 10 60 90 70 36 32 6 98 75 59 4 22 13 95 63 47 29 78 37 66 20 38 27 52 73 67 53 58 55 34 76 2 61 71 87 17 69 9 7 80 35 30 64 84 25 8 1 26 49 24 11 91 21 82 16 88 83 94 89 51 41 33 23 85 40 99 31 81 86 45 57 12 77 72 15 56 48 19 92 46 14 54 3 97 5 62 43 28 44 96 100 93

[MarshallSc]

Thanks alot Walter, this is a very good method as well.

Answer 3

[Azza Hamdi]

% MATRIX X

X=[73 80 75 1; 93 88 93 1; 89 91 90 1; 96 98 100 1; 73 66 70 1; 53 46 55 1; 69 74 77 1; 47 56 60 1; 87 79 90 1; 79 70 88 1; 69 70 73 1; 70 65 74 1; 93 95 91 1; 79 80 73 1; 70 73 78 1];

% Matrix Y

Y=[152; 185; 180; 196; 142; 101; 149; 115; 175; 164; 141; 141; 184; 152; 148];

% Transpose of matrix X

x = X.';

% multiply Matrix X by the tranpose

B=X*x;

% inverse of multiplication

% pinv(A) is a pseudoinverse of A. If Ax = b does not have an exact solution, then pinv(A) returns a least-squares solution.

V=pinv(B);

% V=B^(-1);

% MATRIX X

X=[73 80 75 1; 93 88 93 1; 89 91 90 1; 96 98 100 1; 73 66 70 1; 53 46 55 1; 69 74 77 1; 47 56 60 1; 87 79 90 1; 79 70 88 1; 69 70 73 1; 70 65 74 1; 93 95 91 1; 79 80 73 1; 70 73 78 1];

% Matrix Y

Y=[152; 185; 180; 196; 142; 101; 149; 115; 175; 164; 141; 141; 184; 152; 148];

% Transpose of matrix X

x = X.';

% multiply Matrix X by the tranpose

B=X*x;

% inverse of multiplication

% pinv(A) is a pseudoinverse of A. If Ax = b does not have an exact solution, then pinv(A) returns a least-squares solution.

V=pinv(B);

% V=B^(-1);

% Hat matrix

H=V*X*x;

% to find estimate parameter BETA

Q=x*V*Y;

% predicted

y=H*Y;

% Q=y./X;

% to estimate error

% unit matrix

I=eye(15,15);

% error

e1=I-H;

e=e1*Y;

% e2=Y-y;