<!-- Release notes generated using configuration in .github/release.yml at v1.5 -->
What's Changed
This new version of pysal/spreg brings several new features, performance enhancements and bug fixes. The main contributors to this new version are Luc Anselin, Pedro Amaral, Renan Serenini and Lisa Singh.
Updates
1- Introduction of the DGP module
* The DGP module allows for the creation of spatial models for specific Data Generation Processes (DGP) to support simulation exercises. These include the creation of error term vectors (classic and spatial), dependent and independent variables, spatially correlated or not, and other elements for OLS, SAR, SLX, SDM, SARAR models, etc.
2- Introduction of new specification tests
* The Koley-Bera (2024) tests for WX and SDM, and their variants, have been included in the diagnostics suite.
The Common Factor Hypothesis test has been added to Spatial Durbin Models (GM and ML).
3- Impact estimation
* The estimation of average direct impact (ADI), average indirect impact (AII), and average total impact (ATI) in summary results has been added to models with a spatial lag of the dependent variable.
4- Endogenous Spatial Regimes estimation
* Methods for endogenous spatial regimes estimation based on Anselin and Amaral (2023) have been added, such as OLS_Endog_Regimes and GM_Lag_Endog_Regimes.
5- A flag to allow for the printing of the table with the coefficients' results and their inference straight in LaTeX format
6- Skater_reg now allows for the estimation of Spatial Lag models with a common spatial lag across regimes. A method adapted from Mojena (1977)'s Rule Two has also been introduced to find the optimal number of regimes for the endogenous spatial regimes models.
Bug Fixes
* Several minor performance enhancements and bug fixes.
**Full Changelog**: https://github.com/pysal/spreg/compare/v1.4.2...v1.5