Open joethorley opened 2 years ago
Note that the BurrIII distribution c and k parameters are dependent on the data scaling. This is the cause of the undesirable behavior in Burrlioz, which sometimes results in a different distribution depending on the units (micrograms versus millegrams), for example.
A solution to this is to rescale the data relative to the maximum value for this distribution by default. Suggest this is done by default for the ssd_fit_burrlioz function. How to handle this else-wise needs discussion.
It would be good to know how to set the boundaries for the burrIII with rescaled data. This could potentially be done using a simulation study, based on the three distributions.
Note also a better solution to rescaling is to have an algorithm that determines appropriate smart boundaries given the data range.
ie make sure not hitting 0.05 before other shape parameter hits 20