Pytwoway

-Switch BLM to use variance instead of sds as weights

-Slight speedups to BLM and dynamic BLM

-Fix progress bar for BLM

-Switch from `G'wG` to groupby-sum in BLM (approximately 2x faster overall than before)

-Add option to compute certain operations using GPU for BLM

-Move CHK event studies from BipartitePandas into PyTwoWay

-Add option to compute standard errors and clustered standard errors for continuous control variables in AKM estimation

-Fix bug with Jacobi preconditioner if any diagonal elements equalled 0

-Change parameter dictionaries to import from ParamsDict rather than BipartitePandas

-Add dynamic BLM (not yet added to documentation)

-Add interacted BLM (not yet added to documentation)

-Other small changes and bug fixes

Latest
-Fix FEControlEstimator to normalize categorical variables correctly (normalize the first type for each categorical variable)

-Change FEEstimator and FEControlEstimator to normalize the first firm rather than the last firm

Thank you to Alalalalaki for pointing out the error with normalizing categorical variables and to santiagohermo for suggesting to use releases!