Crate inferust 

inferust

Statistical modeling for Rust - a statsmodels-inspired library.

Modules

Module	Contents
regression	OLS/WLS/GLS/FGLS, quantile regression, plus rolling and recursive OLS with fast/stable/HAC solvers, HC0-HC3 and Newey-West SEs, confidence intervals, influence diagnostics, full summary, and Ridge/Lasso/ElasticNet regularization
glm	Binary logistic, Poisson, and Gamma regression with Wald inference, LRT, residual diagnostics, prediction intervals, classification metrics
gam	Gaussian additive models with spline basis expansion
gmm	Instrumental variables / 2SLS econometrics starter
survival	Kaplan-Meier estimator, log-rank test, Cox proportional hazards regression
statespace	Scalar Kalman filter and local-level state-space model
time_series	ARIMA/SARIMA/SARIMAX via CSS or exact state-space MLE, VAR/VECM/VARMAX, AR, ACF/PACF, Ljung-Box, ADF unit root, KPSS stationarity, Granger causality, Engle-Granger cointegration
hypothesis	t-tests, chi-squared, ANOVA, Tukey HSD post-hoc, multiple-testing corrections (Bonferroni/Holm/BH/BY), Mann-Whitney U, Kruskal-Wallis, Wilcoxon signed-rank, sign test, KS tests, Shapiro-Wilk, Anderson-Darling, Lilliefors, Wald linear-restriction tests
contingency	2x2 tables, odds/risk ratios, McNemar, CMH
diagnostics	VIF, Breusch-Pagan, White, and RESET diagnostics
discrete	Probit, ordered logit, negative binomial, multinomial logit, and zero-inflated Poisson
glm_family	Generic Gaussian/Binomial/Poisson/Gamma GLM front-end
multivariate	MANOVA and PCA starters
imputation	Mean imputation and MICE-style chained equations
treatment	Propensity scores, IPW treatment effects, and balance diagnostics
evaluation	Regression/classification metrics and bootstrap intervals
graphics	Dependency-light SVG plots for lines, scatter, residuals, and ACF bars
plot	Full-featured SVG/ASCII plot builder: line, scatter, bar, step, band, ACF, survival, and residual charts
robust	Huber robust linear regression
gee	Independence-working-correlation GEE
mixed	Random-intercept mixed linear model
descriptive	Summary stats (mean, std, skewness, kurtosis, quartiles)
data	Named-column DataFrame with formula API: y ~ C(g) + x1*x2 - 1 + offset(e)
correlation	Pearson, Spearman, correlation matrices

OLS covariance options

regression::Ols defaults to classical (homoskedastic) standard errors. Switch with .robust() (HC1), .with_covariance(OlsCovariance::Hc3), or .hac(lags) (Newey-West) for time series regressions.

Formula syntax

data::DataFrame accepts R-style formulas:

• "y ~ x1 + x2" - main effects
• "y ~ x1 + x2 - 1" - no intercept
• "y ~ C(group) + x1" - inline one-hot encoding
• "y ~ x1:x2" - interaction term
• "y ~ x1 * x2" - main effects + interaction
• "y ~ log(x) + sqrt(z)" - numeric transforms
• "y ~ x + offset(exp)" - Poisson offset

For Rust-native ergonomics, the formula! macro turns formula-like tokens into a formula string:

let f = inferust::formula!(y ~ x1 + C(group));
assert_eq!(f, "y ~ x1 + C(group)");

Quick start

use inferust::regression::Ols;

let x = vec![vec![1.0], vec![2.0], vec![3.0], vec![4.0], vec![5.0]];
let y = vec![2.1, 3.9, 6.2, 7.8, 10.1];

Ols::new()
    .with_feature_names(vec!["hours".to_string()])
    .fit(&x, &y)
    .unwrap()
    .print_summary();

Re-exports

pub use error::InferustError;

pub use error::Result;

Modules

contingency

Contingency table statistics.

correlation

data

descriptive

diagnostics

discrete

error

evaluation

gam

Generalized Additive Model starters.

gee

glm

glm_family

gmm

Generalized Method of Moments and instrumental-variable estimators.

graphics

Lightweight plotting helpers that render statistical graphics as SVG.

hypothesis

imputation

Multiple-imputation starters.

mixed

multivariate

Multivariate statistics.

panel

Panel-data estimators.

plot

Plotting utilities — SVG file output and ASCII terminal charts.

polars_bridge

Optional Polars bridge (inferust feature polars).

post_estimation

Unified post-estimation helpers across model result types.

regression

robust

statespace

State-space models and Kalman filtering.

survival

Survival analysis: Kaplan-Meier estimator and Cox proportional hazards regression.

time_series

Time series modelling and diagnostics.

treatment

Treatment-effect estimators and balance diagnostics.

Macros

formula

Build a formula string from Rust tokens.