linreg-core 0.8.1

Lightweight regression library (OLS, Ridge, Lasso, Elastic Net, WLS, LOESS, Polynomial) with 14 diagnostic tests, cross validation, and prediction intervals. Pure Rust - no external math dependencies. WASM, Python, FFI, and Excel XLL bindings.
Documentation 
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{
  "test_name": "Cook's Distance (Python - statsmodels)",
  "dataset": "ToothGrowth",
  "formula": "len ~ supp + dose",
  "distances": [
    0.042396320896594224,
    0.0011852195822804016,
    0.01078387373762028,
    0.023478957848413883,
    0.01781564041413668,
    0.00022368192734651966,
    0.0006027228579871243,
    0.0006027228579871243,
    0.029922653669304064,
    0.012932701366472494,
    0.0009322988380208845,
    0.0009322988380208845,
    1.2741963988970726e-05,
    0.0026543235566334816,
    0.03531872187005596,
    0.0026543235566334816,
    0.002074138076107528,
    0.0004810489260300188,
    0.00825734329718659,
    1.8493188357483298e-05,
    0.0030036428177451246,
    0.05817192939599625,
    0.10343635186629987,
    0.0002140758921515016,
    0.002258384556306203,
    0.0731438740388841,
    0.0034206325592646557,
    0.017305789937134945,
    0.0043255890195833474,
    0.02586118687592801,
    0.0011852195822804055,
    0.05848450261933996,
    0.012868598856143637,
    0.021504476660697807,
    0.00012954104261225904,
    0.018705333709668075,
    0.03842661036564516,
    0.024498714208380765,
    0.0059637985044332775,
    0.021504476660697807,
    0.0003033508397721935,
    0.012511872968497326,
    0.014334421224149279,
    0.0373182800312721,
    0.0006394287971013328,
    0.026146747896376964,
    0.03148476891410408,
    0.003222465875020228,
    0.014159967418304357,
    0.04699759064347594,
    0.01454140839057607,
    0.007690699095620121,
    0.054699590660735556,
    0.024690925343276417,
    0.02136559671821507,
    0.005891947877054908,
    0.007690699095620121,
    0.0030036428177451246,
    0.00048138434690727706,
    0.04492365683038477
  ],
  "p": 3,
  "mse": 17.93956203007519,
  "threshold_4_over_n": 0.06666666666666667,
  "threshold_4_over_df": 0.07017543859649122,
  "threshold_1": 1.0,
  "influential_4_over_n": [
    23,
    26
  ],
  "influential_4_over_df": [
    23,
    26
  ],
  "influential_1": [],
  "max_distance": 0.10343635186629987,
  "max_index": 23,
  "description": "Measures influence of each observation on regression coefficients. Uses statsmodels.stats.outliers_influence.OLSInfluence.cooks_distance."
}