Avatar for the Nixtla user
Nixtla
statsforecast
BlogDocsChangelog

Performance History

Latest Results

arima: compute var_coef once at the reported coefficients and defer it in the search The Hessian is now taken after the fit, in the reported coefficient space (untransformed AR, unrotated xreg), so it needs no gradtrans or rotation mapping and is computed once even when maInvert re-parameterises the MA part. Steps scale with parscale, so regressors whose standard error is far below 1e-3 no longer get a biased Hessian, and _coef_var applies its rank test to the diagonal-normalised matrix, so the cutoff responds to collinearity rather than to units. The Hessian is skipped when the objective is not finite at the optimum, which was the whole cost of the AutoRegressive benchmark regression. arima() gains var_coef=True. auto_arima_f passes False for every candidate and computes the covariance once for the winner through arima_var_coef, which holds the coefficients fixed and differentiates over the estimated ones. The result dict records the method so that function can rebuild the objective. The core.py change was unrelated to this PR and is reverted. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
jmoralez:arima-coef-var
23 hours ago
fix: preserve AutoTheta configuration
DresdenGman:fix/autotheta-preserve-configuration
3 days ago
feat: expose fixed theta parameter
DresdenGman:feature/theta-parameter
3 days ago
fix(mfles): preserve naive fallback scale
DresdenGman:fix/mfles-naive-original-scale
4 days ago

Latest Branches

CodSpeed Performance Gauge
-14%
arima: fix coef stderr#1206
23 hours ago
df8e21d
jmoralez:arima-coef-var
CodSpeed Performance Gauge
0%
2 days ago
7098986
jmoralez:fix/xreg-svd-rotation
CodSpeed Performance Gauge
0%
3 days ago
e4c6b37
dependabot/github_actions/ci-dependencies-3b757a5d15
© 2026 CodSpeed Technology
Home Terms Privacy Docs