Switched to using the statsmodels array api

[jmafoster1]

I switched the regression estimators to use the array API instead of the formula API to make test adequacy faster, since statsmodels doesn't have to parse the formula and build the design matrix for each of the bootstrapped samples.

[github-actions]

🦙 MegaLinter status: ✅ SUCCESS

Descriptor	Linter	Files	Fixed	Errors	Elapsed time
✅ PYTHON	black	32		0	0.97s
✅ PYTHON	pylint	32		0	6.03s

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 97.90%. Comparing base (e262f67) to head (d4765fa).
⚠️ Report is 1 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff             @@
##             main     #379      +/-   ##
==========================================
+ Coverage   97.87%   97.90%   +0.02%     
==========================================
  Files          27       27              
  Lines        1551     1572      +21     
==========================================
+ Hits         1518     1539      +21     
  Misses         33       33              

Files with missing lines	Coverage Δ
...esting/estimation/abstract_regression_estimator.py	96.66% <100.00%> (+0.83%)	⬆️
...ausal_testing/estimation/cubic_spline_estimator.py	97.36% <100.00%> (+0.70%)	⬆️
..._testing/estimation/linear_regression_estimator.py	100.00% <100.00%> (ø)
...esting/estimation/logistic_regression_estimator.py	100.00% <100.00%> (ø)
causal_testing/main.py	100.00% <ø> (ø)

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