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": "DFBETAS (Python - statsmodels)",
  "dataset": "lh",
  "formula": "time ~ value",
  "dfbetas": [
    [
      -0.05902486896537772,
      -4.1290189319577615e-15
    ],
    [
      -0.056339822404863,
      -4.116353469418588e-15
    ],
    [
      -0.053678804678832875,
      -4.1043470984090556e-15
    ],
    [
      -0.12208942452584184,
      0.077256781845401
    ],
    [
      -0.14397370582273397,
      0.10443687307861503
    ],
    [
      -0.23270712965143425,
      0.20972330435733938
    ],
    [
      -0.0742240636338753,
      0.03396185272750119
    ],
    [
      -0.06962172323417025,
      0.031856012664261954
    ],
    [
      -0.007839484122936054,
      -0.033315441561495455
    ],
    [
      -0.1159419828603681,
      0.09074244793073884
    ],
    [
      -0.11559646641549348,
      0.09497046346373891
    ],
    [
      -0.10989184850424791,
      0.0957231928729488
    ],
    [
      -0.06261532051074355,
      0.039622253734633135
    ],
    [
      -0.07878443084765545,
      0.06694595659657264
    ],
    [
      0.22905088888270153,
      -0.27804203207347833
    ],
    [
      0.2145191907078622,
      -0.26040218396059894
    ],
    [
      0.03492164254471729,
      -0.06109129919197176
    ],
    [
      -0.03054823851388464,
      0.019330573534882965
    ],
    [
      -0.024179294914280083,
      0.015300379370471726
    ],
    [
      -0.0032971081915824214,
      0.002708801598824433
    ],
    [
      0.009110701637376333,
      -0.007485069256973587
    ],
    [
      0.037471933996063696,
      -0.03184124629574315
    ],
    [
      0.01397840605650455,
      -0.024453574471223566
    ],
    [
      0.053329892799425745,
      -0.06895818380257586
    ],
    [
      0.005898839479065829,
      -0.002699064263572325
    ],
    [
      0.05066983605519598,
      -0.039656946055814254
    ],
    [
      0.061078916149378666,
      -0.047803653444722365
    ],
    [
      0.005486695144624856,
      -0.007485069256974084
    ],
    [
      -0.0019856020124533074,
      0.0027088015988239356
    ],
    [
      -0.010233380273400362,
      0.01790209309963528
    ],
    [
      -0.013697214296516132,
      0.023961662616921436
    ],
    [
      0.03671274526833919,
      -0.016798229401398492
    ],
    [
      -0.010140453678356028,
      0.027414405563319606
    ],
    [
      0.02315522357583213,
      -4.5077269431798606e-15
    ],
    [
      0.229704061693486,
      -0.19518777985367072
    ],
    [
      0.2964799795956247,
      -0.25825400751815186
    ],
    [
      0.438982987052268,
      -0.39562587849868613
    ],
    [
      0.5369547617609446,
      -0.48985868742216954
    ],
    [
      0.14468834152060434,
      -0.10495526160831194
    ],
    [
      -0.12719673809936985,
      0.1513146640941925
    ],
    [
      -0.15037136254170871,
      0.17382695557777345
    ],
    [
      -0.17148231378177176,
      0.19823088676110015
    ],
    [
      -0.14800100802497845,
      0.18449734930530548
    ],
    [
      -0.02699275798977929,
      0.07297409349481386
    ],
    [
      0.19877261036739108,
      -0.14418736922701983
    ],
    [
      -0.24277636313081571,
      0.28426155001446207
    ],
    [
      -0.16943630587854042,
      0.21908950703400404
    ],
    [
      -0.14747385192950685,
      0.20118704724590408
    ]
  ],
  "n": 48,
  "p": 2,
  "threshold": 0.2886751345948129,
  "influential_observations": [
    36,
    37,
    38
  ],
  "description": "Measures influence of each observation on each regression coefficient."
}