antecedent-stats 0.5.2

Statistical kernels, regression, and linear-algebra backends for the Antecedent causal inference engine; start with the `antecedent` crate
Documentation
//! Statistical algorithms and linear-algebra backends.
//!
//! SPDX-License-Identifier: MIT OR Apache-2.0

#![forbid(unsafe_code)]
#![deny(missing_docs)]

pub mod ci;
pub mod cluster;
pub mod covariance;
pub mod design;
pub mod divergence;
pub mod error;
pub mod faer_backend;
pub mod fdr;
pub mod gam;
pub mod glm;
pub mod gram;
pub mod interference;
pub mod linalg;
pub mod m_estimate;
pub mod matching;
pub mod observation;
pub mod propensity;
pub mod regularized;
pub mod response;
pub mod special;
pub mod twosls;

pub use ci::{
    BayesFactorCi, CalibrationReport, CiBatchRequest, CiBatchResult, CiPreparationPlan, CiQuery,
    CiResult, CiWorkspace, ConditionalIndependence, ConditionalIndependenceTest, ConfidenceMethod,
    GSquared, Gpdc, KnnDependence, KnnDependenceWorkspace, MixedKnnDependence,
    MultivariatePartialCorrelation, OracleCi, PairwiseMultivariateCi, PartialCorrelation,
    PosteriorDependenceCi, PosteriorPredictiveCi, PreparedCiTest, RegressionCi,
    RobustPartialCorrelation, SignificanceMethod, SymbolicCmi, WeightedPartialCorrelation,
    analytic_confidence_level, analytic_parcorr_ci, calibrate_parcorr_like, ci_from_name,
    nonparametric_permutation_count, pairwise_multivariate_test,
};
pub use cluster::{
    MAX_CLUSTER_DIMENSIONS, bartlett_weight, combine_inclusion_exclusion, effective_nw_lag,
    intern_cluster_tuples, multiway_subset_masks, multiway_subset_sign, panel_hac_meat_matrix,
    panel_hac_meat_scalar,
};
pub use covariance::{SandwichKind, coefficient_covariance, score_coefficient_covariance};
pub use design::{
    BasisKind, CompiledDesign, ContrastCodingKind, DesignColumn, DesignColumnMap, DesignColumnRole,
    RecordedContrast, RecordedSmooth, StandardizationRecord, StandardizedColumn,
    standardize_columns,
};
pub use divergence::{
    change_point_known_split, change_point_scan, change_point_two_sample, classifier_two_sample,
    gaussian_kl, kernel_two_sample, max_abs_cusum, mean_diff_two_sample, mean_var,
    residual_likelihood_ratio, sample_std,
};
pub use error::StatsError;
pub use faer_backend::FaerBackend;
pub use fdr::{
    FdrAdjustment, MultipleTestingMethod, adjust_pvalues, benjamini_hochberg, benjamini_yekutieli,
    bonferroni, holm,
};
pub use gam::{
    GamFit, GamOptions, GamWorkspace, SmoothSpec, compile_additive_design, expand_bspline, fit_gam,
    fitted_from_gam, predict_gam,
};
pub use glm::{
    DEFAULT_RIDGE_ON_SEPARATION, GlmDesignRef, GlmFamily, GlmFit, GlmOptions, MultinomialDesignRef,
    MultinomialFit, NbAlphaPolicy, fit_glm, fit_glm_ridge, fit_multinomial_logit,
};
pub use gram::{
    accumulate_xtx, accumulate_xtx_xty_row, chol_log_det, chol_solve, cholesky_spd, form_xtx,
    invert_square,
};
pub use interference::{
    ExposureProbabilities, ExposureProbabilityMethod, RandomizationContrast, RandomizationMean,
    exposure_probabilities, exposures, randomization_contrast, randomization_mean,
};
pub use linalg::{DenseLinearAlgebra, FitDiagnostics, LeastSquaresFit, LeastSquaresWorkspace};
pub use m_estimate::{MEstimateFit, MEstimateOptions, fit_huber_m};
pub use matching::{
    EXACT_MATCHING_ROW_LIMIT, MatchingDistance, MatchingIndex, nearest_euclidean_scalar,
};
pub use observation::{
    GaussianObservation, ObservationProbabilityFit, fit_observation_logistic,
    gaussian_observation_log_likelihood, kaplan_meier_ipcw, selected_outcome_pseudo_values,
};
pub use propensity::{
    PropensityFit, PropensityWorkspace, fit_propensity, fit_propensity_diagnostic,
    fit_propensity_in_place, predict_propensity,
};
pub use regularized::{
    LassoFit, LassoOptions, fit_lasso, fit_lasso_with_ones_column, fit_ridge, predict_lasso,
};
pub use response::{
    LocalPolynomialInfluence, LocalPolynomialPoint, gaussian_density, gaussian_local_quadratic,
    gaussian_local_quadratic_influence, silverman_bandwidth,
};
pub use special::{
    digamma, gamma_q, ln_gamma, normal_ppf, regularized_incomplete_beta, student_t_ppf,
    student_t_sf, trigamma,
};
pub use twosls::{FirstStageDiagnostics, TwoSlsFit, fit_2sls, fit_wls};