Efficient memory allocation for MonteCarlo simulation
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Hi, I am a beginner with Matlab and have an issue, maybe someone can help I need to perdorm a MC simulation, I have data for 8760 hours (1 year), i need to create a normal distribution for a variable Vf, and run the code at least 10000 times,
The code is like
n=10000;
L=length(data_es1);
for i=1:1:n
%L is 8760, data_es1(j,2) is the mean while data_es1(j,12) is st.deviation
for j=1:1:L
Vf(j,i)=data_es1(j,2)+data_es1(j,12).*randn;
end
This would create a 10000x8760 matrix, that is very big, and I have several variables to manage in this way (Vf plus at least 5 others), I have encourred a "out of memory" problem,
Any idea to run the code smarter and save memory/busy problems?
Thank you
Alex
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