Stata-class statistics, GPU-accelerated by Apple Silicon. Native Swift — no Electron, no Python runtime, no compromises.
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Wed, Aug 5, 2026 6
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feat: v1.0 features — sample datasets, docs site, Metal 2M-point renderer
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- sysuse command with bundled samples (sales: 200-firm x 5-year panel; mtcars) shipped as ZQEngine resources, generated by scripts/make_samples.R - metrika-cli docs: static documentation site rendered from the shared command registry (docs/index.html, 38 commands, light/dark); CLI restructured with a default 'run' subcommand - Metal point-sprite renderer (CLAUDE.md §7 pane 4): packed 12-byte vertices, unified-memory buffer written once, scroll-pan / pinch-zoom / double-click-reset touching only a 24-byte uniform; takes over scatter plots past 100k points (METRIKA_METAL_THRESHOLD override for tests); verified rendering 2,000,000 points in-app - METRIKA_AUTORUN debug hook for headless app driving - MARKETING_VERSION 1.0.0 - 116 kit tests + 4 UI tests green Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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feat(stats): gradient-boosted regression trees (boost command)
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- ZQGradientBoosting: exact-greedy trees cloning xgboost's algorithm — gain 1/2[GL2/(HL+l) + GR2/(HR+l) - G2/(H+l)] - gamma, leaf -G/(H+l), midpoint splits between consecutive distinct values, missing rows default left, pre-sorted feature indices; squared loss, deterministic (no subsampling) - engine: 'boost y x…, rounds(#) [eta() maxdepth() lambda()]' reporting training R2/RMSE with an in-sample caveat; model stored in the estimation state (Kind.boost) so predict routes through the trees (missing features follow the default direction); margins and GLM statistics refused after boost - validation: per-observation prediction parity with R xgboost 3.2 (exact method, base_score = mean) at 1e-4 (xgboost is float32 internally); a stump finds the exact midpoint split with lambda 0; training loss decreases monotonically in rounds - manual entry + coverage test - 115 tests green (swift test and xcodebuild with GPU suites) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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feat(stats): Bayesian linear regression via Gibbs sampling (bayes prefix)
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- PhiloxStream in ZQGPU: sequential variate stream over a dedicated counter block (bit 62 + per-stream 2^48 words, disjoint from bootstrap and permutation streams); Box-Muller normals, Marsaglia-Tsang gammas (moments verified against theory at 200k draws) - ZQBayesianRegression: semi-conjugate Gibbs with Stata bayes default priors (coefficients N(0, 10000), variance InvGamma(.01, .01)); exact full conditionals via dense Cholesky; posterior mean/sd and equal-tailed 95% credible intervals; ZQStats now depends on ZQGPU for the shared RNG - engine: 'bayes [, mcmcsize() burnin() seed() normalprior()]: reg …' with reproducible chains; manual entry included - validation: with diffuse priors the posterior reproduces OLS (mean within 5% of a posterior SD, sd ratio in [0.9, 1.15], CrI brackets the estimate, sigma recovers the DGP); tight priors shrink toward zero; chains bit-reproducible per seed - 111 tests green (swift test and xcodebuild with GPU suites) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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feat(app): user manual — in-app reference and console help
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- ZQCommandReference: one registry of every command (syntax, options, examples, notes) shared by the console and the app so they cannot drift; 35 commands across 10 categories - console: 'help' lists the reference by category, 'help <command>' (abbreviations resolve too) renders the full entry - app: Manual pane — searchable sidebar grouped by category, per-command pages (syntax/options/examples), and a 'How Metrika works' overview covering the command grammar, data handling, estimation conventions, the CPU/GPU planner, reproducibility, and user commands - release plumbing: real team ID + notary keychain-profile NAME in release.sh (both configuration, not credentials, per the security conventions), manual Developer ID signing with hardened runtime, -skipPackagePluginValidation, DMG background art - tests: help coverage test pins a manual entry for every implemented verb; UI smoke drives the Manual pane; 106 green Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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feat(stats): logit/probit/poisson MLE, tabulate, correlate
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- ZQGLM: Fisher-scoring IRLS through the LAPACK QR path (X'WX never formed), converged to |Δll| < 1e-13; classical, robust (HC0 score sandwich, Stata ML convention), and cluster (G/(G−1)) VCE; LR/Wald chi2, McFadden pseudo-R²; information matrix re-evaluated at the converged beta (R's vcov carries last-iteration weights and is only ~1e-6-accurate by its own stopping rule — fixtures compute expected information at the optimum explicitly) - Distributions: regularized incomplete gamma, chi-square CDF/p-value, normal quantile - ZQCorrelate: Pearson matrix on listwise-complete data - Engine: logit/probit/poisson tables (z, P>|z|, LR chi2, pseudo R²), one-way and two-way tabulate with totals, Stata-style lower-triangle correlate - Fixtures: binomial/poisson outcomes drawn after existing draws (earlier golden values bit-identical); glm at epsilon 1e-12 - 56 tests green (12 new) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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feat: bootstrap Metrika v0.1 skeleton with working ZQL vertical slice
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- MetrikaKit SPM package: ZQParser, ZQPlanner, ZQEngine, ZQData, ZQStats, ZQGPU, ZQGraphics, ZQPlugins (Swift 6, strict concurrency) - ZQL parser: lexer, Pratt expressions, factor variables, prefix commands, column-cited errors with Levenshtein verb suggestions - ZQData: DuckDB-backed load/save (parquet, csv, json, arrow) - ZQStats: OLS via LAPACK QR, HC0-HC3 and cluster-robust SE, summarize, t/F distributions accurate in the far tails - ZQGPU: Philox4x32-10 reference RNG, counter-addressable bootstrap - ZQEngine: session actor with use/save/gen/replace/drop/keep/summarize/ regress/count/list/graph/bootstrap/set seed/xtset/log - SwiftUI app (xcodegen): console with history, variables sidebar, Swift Charts plots; sandboxed + hardened runtime entitlements - Tests: 44 green (parser golden, R fixtures at 1e-10, Philox KAT, end-to-end engine); Tests/Fixtures/generate.R; Tests/Bench harness - scripts: check_headers.sh + pre-commit hook, make_icns.sh, release.sh Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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