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The MaxEnt algorithm implemented in find.density() shows convergence problems in some cases.
For example, I've noticed that if one extrapolates series of raw moments too far into the future (> 50 time steps) with a multivariate random walk w drift the likelihood of a failure to converge and estimate a density out of those moments is high.
And I think, this has to do with the way one extrapolates the moments and keeps them within the adequate range.
The fix should come as follows:
Find a better way to extrapolate the moments so that they always make sense, or;
Find a way to train the algorithm to discard the importance of the higher order moments when these tend to cause problems. Because the higher the moment the less important it is in the reconstruction of the density.
The text was updated successfully, but these errors were encountered:
The MaxEnt algorithm implemented in
find.density()
shows convergence problems in some cases.For example, I've noticed that if one extrapolates series of raw moments too far into the future (> 50 time steps) with a multivariate random walk w drift the likelihood of a failure to converge and estimate a density out of those moments is high.
And I think, this has to do with the way one extrapolates the moments and keeps them within the adequate range.
The fix should come as follows:
The text was updated successfully, but these errors were encountered: