- Fix y (power, I assume) to some value
- Get a vector of x that corresponds to y (e.g. +/- 5%)
- Let's call this vector x_target. You may then use the "ecdf" function to obtain an empirical PMF of this vector, as follows:
Probability of obtaining x when giving y
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André Bernal García
el 23 de Abr. de 2017
Respondida: israt fatema
el 3 de Ag. de 2021
I have a data set of Power, depending on wind . The data looks like this:
I want to calculate the following:
For a certain velocity ( x axis) = 9 There is a probability of 90% that the values are in between 0.9 & 1 for example.
The purpose is to make after a forecast where I will have a certain velocity and I have to provide a power.
Thanks in advance
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David Ding
el 27 de Abr. de 2017
Editada: David Ding
el 27 de Abr. de 2017
Hi Andre,
Based on your description, it looks like you are looking for an empirical probability mass function (PMF) to fit the given data. You can achieve this via the "ecdf" function.
For example, based on what I understand of your workflow, you can do something like the following:
[f, pts] = ecdf(x_target)
Next, you may plot the empirical PMF as follows:
figure();
plot(pts, f);
xlabel('Wind Speed');
ylabel('PMF');
A similar approach can be followed if you want to fix x to analyze y.
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israt fatema
el 3 de Ag. de 2021
Hi, i am interested about the problem you have mentioned here. Would you like to share your outcome if you could have managed to solve it?
Thanking you.
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