---------- C:\TESTXLS\EXLISAMP.XLS
bindata;
1. Transfer the data to MATLAB.
<== MLPutMatrix("data",DATA)
2. Set up data for regression.!
<== MLEvalString("y = data(:,3)"),
<== MLEvalString("e = ones(length(data),1)")'
<== MLEvalString("A = [e data(:,1:2)]")#
5. Compare original data with regression results.#
<== MLEvalString("n = size(data,1)")C
<== MLEvalString("plot(1:n,y,'bo',1:n,fit,'r:',1:n,newfit,'g'); legend('data','fit','newfit')")"
1. Transfer original data to MATLAB.
2. Transfer interpolation data points to MATLAB.
3. Execute MATLAB data interpolation function.C
<== MLEvalString("[XI, TI, VI] = griddata(X,T,V,Xa,Ta, 'invdist')")<
4. Transpose output data matrix and transfer data to Excel.
5. Plot interpolated data and label the figure.}
bindata
1. Transfer data to MATLAB.
<== MLPutMatrix("b", bindata)
3. Transfer output data to Excel."
4. Plot efficient frontier data and label the figure.X
1. Transfer data to MATLAB.&
4. Transfer output data to Excel.
data#
y = data(:,3)Bے
e = ones(length(data),1)Bے
A = [e data(:,1:2)]Bے
n = size(data,1)Bے
plot(1:n,y,'bo',1:n,fit,'r:',1:n,newfit,'g'); legend('data','fit','newfit')Bے
[XI, TI, VI] = griddata(X,T,V,Xa,Ta, 'invdist')Bے
data
y = data(:,3)
A = [e data(:,1:2)]
plot(1:n,y,'bo',1:n,fit,'r:',1:n,newfit,'g');legend('data','fit','newfit')A@
Partager