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Summary:
A diagnostic symbolic adjustment layer for simple DSGE models. Features a built-in linearized DSGE engine constructed from symbolic expressions. Functionality is included to regress on measurement equations with symbolic function discovery using Kalman Filter innovations. The library is designed to be a diagnostic tool to provide isight into potential model misspecifications through said mesaurement regressions.
Latest version:
1.2.0
Required dependencies:
matplotlib
|
numba
|
numpy
|
pandas
|
pysr
|
pyyaml
|
scipy
|
statsmodels
|
sympy
Optional dependencies:
fredapi
|
python-dotenv
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