spb/metrika Public
Stata-class statistics, GPU-accelerated by Apple Silicon. Native Swift — no Electron, no Python runtime, no compromises.
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feat(engine): predict with estimation state (e() analog)
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- PredictorDefinition (column / indicator / product / constant) records how each fitted regressor is recomputed from the dataset; threaded through buildRegressionSample so factor expansions and interactions carry their recipes - EstimationState stored after regress, logit/probit/poisson, and ivregress; cleared after xtreg (predict there needs the estimated u_i) - predict newvar [, xb | residuals | pr | n]: evaluates over ALL current observations with missing propagation; kind-aware defaults (xb for ols/iv, pr for logit/probit, n for poisson) and statistic validation - ZQFactorExpansion.expand now returns the numeric level alongside each indicator column - tests: xb + residuals reconstruct the response exactly (plain and factor models), mean fitted probability/count equals ybar (score equations), option validation; 93 green Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>