Releases: pzivich/Delicatessen
v2.2
v2.1
v2.1 addition of new estimating equations: Rogan-Gladen measurement error correction, multinomial logistic regression, efficient g-estimation, log-linear SMM g-estimation.
Added support for Python 3.12
Added option to rescale spline terms when generated
Re-organized test structure for easier maintenance (does not impact actual package)
Bug fixes: fixed issue in call to ee_lasso_regression
v2.0
v1.4
Additions of v1.4 release
- Added Generalized Linear Models (GLM) as a built-in estimating equation
- Added Z-scores, P-values, and S-values
- Added Marginal Structural Models with Inverse Probability Weighting as a built-in estimating equation
- Added support for missingness weights with
ee_ipw
andee_gestimation_snmm
v1.3
v1.2
v1.1
v1.0
v1.0 release
This major release changes the version support for several items. In order to speed up the computation of the bread matrix, SciPy approx_fprime funtionality is now used. This required the following version changes:
- SciPy v1.9.0+ which requires NumPy 1.18.5. This is a major change in the supported versions
- SciPy v1.9.0 also necessitates the reduction of support to 3.8+
The regression estimating equations have also now been fully updated to the new syntax. The legacy versions have been removed.
v0.6
v0.5
v0.5 adds the optional subset
parameter which allows a user to optimize only a subset of the parameters (during the root-finding phase). This is useful when combined with pre-washing steps (pre-washing is essential for proper use of the subset
functionality).
- IGNORE the 0.5.0 tag. This is a GitHub issue (it things v0.5 is an existing tag, which it is not)