Release 4.13

This is a feature and bug release.

• Added AbsorbingLS which allows a large number of variables to be absorbed. This model can handle very high-dimensional dummy variables and has been tested using up to 1,000,000 categories in a data set
  with 5,000,000 observations.
• Fixed a bug when estimating weighted panel models that have repeated observations (i.e., more than one observation per entity and time id).
• Added drop_absorbed option to PanelOLS which automatically drops variables that are absorbed by fixed effects.
• Added optional Cythonized node selection for dropping singletons
• Added preconditioning to the dummy variable matrix when use_lsmr=True in fit. In models with many effects, this can reduce run time by a factor of 4 or more.