Ensemble distribution gbd and vivarium comparisons, XMIN and XMAX #1241
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alibow
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aflaxman,
rmudambi,
zmbc,
NathanielBlairStahn,
pletale and
SylLutze
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docs/source/model_design/general_reference_material/ensemble_distributions/index.rst
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| that can return unexpected results. The python function appears to solve the | ||
| distribution algebraically rather than via optimization and therefore does not |
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The implementation of get_params in risk_distribution.py appears to use algebra to compute the mean and variance of an inverse Weibull distribution with given parameters, but it feeds this information into an optimization routine to do the reverse operation, i.e., to find the correct distribution parameters for a given mean and standard deviation.
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Oh, darn, I see. Maybe it's just that the specific mean/standard deviation I used returned expected results with the python optimization function but not the R optimization function, then. I guess we should run some tests with random mean/sds to see if we get funky behavior with python sometimes too
docs/source/model_design/general_reference_material/ensemble_distributions/index.rst
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…istributions/index.rst Co-authored-by: Nathaniel Blair-Stahn <ndbs@uw.edu>
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