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
{
  "test_name": "DFBETAS (Python - statsmodels)",
  "dataset": "longley",
  "formula": "GNP.deflator ~ GNP + Unemployed + Armed Forces + Population + Year + Employed",
  "dfbetas": [
    [
      -0.1879751812186725,
      0.04220760916649971,
      -0.13010174506428898,
      -0.1533212945189497,
      -0.33053614414511107,
      0.1929623060702137,
      -0.2662374809281175
    ],
    [
      0.02704072037359524,
      0.20093856800953425,
      -0.1502161953255685,
      -0.5203013729419871,
      -0.16167951688767412,
      -0.02238000153026637,
      -0.1858684426564058
    ],
    [
      0.0029137596887657594,
      -0.005814106755282198,
      0.010595373765063362,
      0.007242239467279236,
      0.008613493717784955,
      -0.0030560794197868595,
      0.006714957136599152
    ],
    [
      0.8571498346427274,
      0.45395275645555777,
      0.808442994637149,
      0.9958314405723259,
      0.2636870549741833,
      -0.8641883711153461,
      0.9459848072035418
    ],
    [
      -0.6231471124547735,
      -0.7031394849856718,
      -0.5699395964933991,
      -0.47023904037037606,
      0.3517068800119579,
      0.6178650675612198,
      -0.32230931670445806
    ],
    [
      -0.020537313978563555,
      0.0485804164206691,
      -0.043300503784495153,
      -0.015325915082801799,
      -0.06551521687505989,
      0.02230154553283247,
      -0.10216209877941505
    ],
    [
      -0.39910196527539815,
      -0.5405714444913466,
      -0.47643824373209565,
      -0.11978198982744424,
      0.4711686502809477,
      0.3933774740773504,
      -0.22642878981118694
    ],
    [
      -0.024207397780015825,
      -0.049165852686369006,
      -0.007355665994739301,
      0.0393870613694886,
      0.04320910127204342,
      0.023543530841755245,
      -0.0024171818292791024
    ],
    [
      0.2681584705741352,
      0.22202765617257675,
      0.16504612033864222,
      0.06987031863431291,
      0.18064433794109852,
      -0.2682194662721729,
      0.04061408252305083
    ],
    [
      -0.12489088028948821,
      0.07443608946558171,
      -0.19731167990250817,
      -0.2277953464253923,
      -0.046377248064628326,
      0.12960802927743217,
      -0.4372167285107481
    ],
    [
      -0.23738366673588535,
      -0.24061375844954921,
      -0.20337873998696573,
      -0.20900983242657376,
      -0.041838359544882665,
      0.23581593718631802,
      -0.0016316355546471006
    ],
    [
      0.01591771045403277,
      0.17445754739549493,
      0.21128122959223142,
      0.10366451686714193,
      -0.40483649191489324,
      -0.011165667483114327,
      -0.03823967178035579
    ],
    [
      0.024600685213097686,
      -0.11532116387994656,
      0.010782474026060796,
      0.1204353233006624,
      0.24031048043083522,
      -0.0280287410647081,
      0.08879211871447533
    ],
    [
      -0.03375921893176698,
      -0.01134970117925046,
      -0.03135240776121781,
      -0.05761147707519023,
      -0.028863934936811893,
      0.03407561840418543,
      -0.02496415304206347
    ],
    [
      0.13079602454299757,
      0.06627511059912304,
      0.12917520347420997,
      0.13153487661438842,
      0.07197808061428723,
      -0.13192150664758592,
      0.1206718100544692
    ],
    [
      0.11923868591524943,
      0.18646269611184166,
      0.41900797859736993,
      0.28062246538786434,
      -0.7414808936230289,
      -0.11553217894038417,
      0.43432787977641
    ]
  ],
  "n": 16,
  "p": 7,
  "threshold": 0.5,
  "influential_observations": [
    2,
    4,
    5,
    7,
    16
  ],
  "description": "Measures influence of each observation on each regression coefficient."
}