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": "DFFITS (Python - statsmodels)",
  "dataset": "synthetic_interaction",
  "formula": "x1 ~ x2 + y",
  "dffits": [
    -0.594694669130564,
    -0.050188622209265905,
    -0.20413896217743896,
    0.03140036934069803,
    -0.36575116710211264,
    -0.16466993301556496,
    0.11760180601704273,
    0.028415201389304156,
    0.047603211194435724,
    0.6332998291948877,
    0.23005409569295668,
    0.053843391151610624,
    -0.28811482262602833,
    0.14993750845421566,
    0.0185325159350704,
    0.14348637056345181,
    -0.004916213789322712,
    0.1481437034378674,
    -0.47129051556882834,
    0.09520372005071502,
    -0.21450620174704307,
    0.1760865798067526,
    -0.12274206704681363,
    0.057203777704338196,
    0.011292440379289548,
    -0.1873608198579518,
    0.1597764032623442,
    -0.05217528125291794,
    -0.14732021082275287,
    0.11782160198374755,
    0.015796700968024557,
    0.2504989114462302,
    -0.012759238967771036,
    -0.01282201234429653,
    0.07766368281772572,
    -0.17107217101545383,
    0.5452802236326135,
    0.15573085602341225,
    0.01298899449909832,
    -0.042498694335835425,
    0.06091096060231256,
    0.01520835925163323,
    0.04149616309723898,
    0.01998007257563219,
    0.1549821940353979,
    0.057214522852212235,
    -0.1256908659263881,
    -0.17799185359355146,
    0.05686632889300344,
    -0.21058712609556884,
    0.0654622797005201,
    -0.04857571866506774,
    0.01805648606519628,
    0.09601565938022684,
    -0.23464691502191043,
    -0.11535579785305665,
    0.35717774763406,
    -0.13051093114248127,
    -0.1067521983429159,
    0.026210597375205855,
    -0.0053609253053843575,
    0.07149098491117169,
    -0.3052552268972126,
    -0.3094310963182678,
    -0.015046485680428552,
    0.3155132694373327,
    0.01180557333400199,
    0.032005778956713284,
    0.3868399496738269,
    0.00011981304495235118,
    -0.04550253952668269,
    0.013269857521712716,
    0.22733701669391784,
    -0.37661393104976715,
    0.054798820342165315,
    0.029646319700718314,
    -0.17149225158297454,
    0.13872576574100903,
    0.05578189679018952,
    -0.029061110349812326,
    0.06133053714710046,
    0.0077154535561531545,
    -0.39139035838567277,
    0.08379524223770457,
    -0.10113603603826928,
    0.2990681090727629,
    -0.03896835458881106,
    0.17879023662995258,
    0.3006433863313369,
    -0.12182494457623953,
    -0.08686637209161943,
    -0.3362133838468556,
    0.17928926495826342,
    0.1714281630103922,
    -0.455193110491802,
    -0.3007297103698994,
    0.014021693715810432,
    -0.17848881746611975,
    0.04291898767968248,
    0.11107796341657954
  ],
  "n": 100,
  "p": 3,
  "threshold": 0.34641016151377546,
  "influential_observations": [
    1,
    5,
    10,
    19,
    37,
    57,
    69,
    74,
    83,
    95
  ],
  "description": "Measures influence of each observation on its fitted value."
}