crabbymetrics
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  • API
    • API Overview
    • Regression And GLMs
    • OLS
    • Ridge
    • FixedEffectsOLS
    • ElasticNet
    • Logit
    • MultinomialLogit
    • Poisson
    • FTRL
    • Causal Inference And Panels
    • TwoSLS
    • BalancingWeights
    • EPLM
    • AverageDerivative
    • PartiallyLinearDML
    • AIPW
    • SyntheticControl
    • HorizontalPanelRidge
    • SyntheticDID
    • MatrixCompletion
    • InteractiveFixedEffects
    • Transforms
    • PCA
    • KernelBasis
    • Estimation Interfaces
    • GMM
    • MEstimator
    • Optimizers
  • Binding Crash Course
  • Regression And GLMs
    • OLS
    • Ridge
    • Fixed Effects OLS
    • ElasticNet
    • Logit
    • Multinomial Logit
    • Poisson
    • GMM
    • FTRL
    • MEstimator Poisson
  • Causal Inference
    • Balancing Weights
    • EPLM
    • Average Derivative
    • Double ML And AIPW
    • Richer Regression
    • TwoSLS
    • Synthetic Control
    • Synthetic DID
    • Horizontal Panel Ridge
    • Matrix Completion
    • Interactive Fixed Effects
    • Staggered Panel Event Study
  • Transforms
    • PCA And Kernel Basis
  • Ablations
    • Variance Estimators
    • Semiparametric Estimator Comparisons
    • Two-Period Semiparametric DID
    • Bridging Finite And Superpopulation
    • Panel Estimator DGP Comparisons
    • Same Root Panel Case Studies
    • Randomized Sketching And Least Squares
  • Optimization
    • Optimizers
    • GMM With Optimizers
  • Ding: First Course
    • Overview And TOC
    • Ch 1 Correlation And Simpson
    • Ch 2 Potential Outcomes
    • Ch 3 CRE And Fisher RT
    • Ch 4 CRE And Neyman
    • Ch 9 Bridging Finite And Superpopulation
    • Ch 11 Propensity Score
    • Ch 12 Double Robust ATE
    • Ch 13 Double Robust ATT
    • Ch 21 Experimental IV
    • Ch 23 Econometric IV
    • Ch 27 Mediation

On this page

  • 1 Regression and GLMs
  • 2 Causal inference and panels
  • 3 Transforms
  • 4 Estimation interfaces and utilities
  • 5 Compatibility note

API

Class-named pages grouped by modeling task

The API documentation is organized around one page per public Python class. The navigation is opinionated, but the page title is the importable class name.

Each class page has the same contract:

  • where the estimator or helper fits conceptually;
  • the main math or estimating equation;
  • constructor and public methods from the live module;
  • a minimal runnable example;
  • a live summary() schema check where the class has fitted state.

1 Regression and GLMs

  • OLS
  • Ridge
  • FixedEffectsOLS
  • ElasticNet
  • Logit
  • MultinomialLogit
  • Poisson
  • FTRL

2 Causal inference and panels

  • TwoSLS
  • BalancingWeights
  • EPLM
  • AverageDerivative
  • PartiallyLinearDML
  • AIPW
  • SyntheticControl
  • HorizontalPanelRidge
  • SyntheticDID
  • MatrixCompletion
  • InteractiveFixedEffects

3 Transforms

  • PCA
  • KernelBasis

4 Estimation interfaces and utilities

  • GMM
  • MEstimator
  • Optimizers

5 Compatibility note

Older example and ablation pages remain in the site because they are useful worked examples. The class pages above are the canonical API docs.