Matlab analysis of geographical data
2016-08-23
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%Markov chain
% The first method
A=[0 1243.37 171.92 29.79 0 0 0
957.97 0 0 0 6983.97 0 0
9812.96 0 0 203845.5 0 0 0
34-0 77259.28 3851.17 0-4.89
128.47 11580.83 0 5761.7 2397.61 0
2293.52 9979.07 0 91339.8 24.36
0 141.18 2.2 0 0 28.67]; % The original data matrix
[m,n]=size(A); Rate counts the number of rows and columns of a matrix
Rsum=sum(A\'); % Sum of matrices each row values
S=Rsum(ones(n,1),:); % ROWCOUNT values and pan as matrix
M=(A\'./S)\'; Rate of transition probability matrix
% The second method
A=[0 1243.37 171.92 29.79 0 0 0
957.97 0 0 0 6983.97 0 0
9812.96 0 0 203845.5 0 0 0
34-0 77259.28 3851.17 0-4.89
128.47 11580.83 0 5761.7 2397.61 0
2293.52 9979.07 0 91339.8 24.36
0 141.18 2.2 0 0 28.67]; % The original data matrix
[n,m]=size(A); Rate counts the number of rows and columns of a matri
% The first method
A=[0 1243.37 171.92 29.79 0 0 0
957.97 0 0 0 6983.97 0 0
9812.96 0 0 203845.5 0 0 0
34-0 77259.28 3851.17 0-4.89
128.47 11580.83 0 5761.7 2397.61 0
2293.52 9979.07 0 91339.8 24.36
0 141.18 2.2 0 0 28.67]; % The original data matrix
[m,n]=size(A); Rate counts the number of rows and columns of a matrix
Rsum=sum(A\'); % Sum of matrices each row values
S=Rsum(ones(n,1),:); % ROWCOUNT values and pan as matrix
M=(A\'./S)\'; Rate of transition probability matrix
% The second method
A=[0 1243.37 171.92 29.79 0 0 0
957.97 0 0 0 6983.97 0 0
9812.96 0 0 203845.5 0 0 0
34-0 77259.28 3851.17 0-4.89
128.47 11580.83 0 5761.7 2397.61 0
2293.52 9979.07 0 91339.8 24.36
0 141.18 2.2 0 0 28.67]; % The original data matrix
[n,m]=size(A); Rate counts the number of rows and columns of a matri
matlab
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