causaldef - Decision-Theoretic Causal Diagnostics via Le Cam Deficiency

Implements Le Cam deficiency theory for causal inference, as described in Akdemir (2026) <doi:10.5281/zenodo.18367347>. Provides theorem-backed bounds together with computable proxy diagnostics for information loss from confounding, selection bias, and distributional shift. Supports continuous, binary, count, survival, and competing risks outcomes. Key features include propensity-score total-variation deficiency proxies, negative control diagnostics, policy regret bounds, and sensitivity analysis via confounding frontiers.

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5.34 score 181 downloads

STPGA - Selection of Training Populations by Genetic Algorithm

Advanced genetic algorithms for optimal subset selection in high-dimensional prediction problems. Provides efficient single and multi-objective optimization for training population selection with comprehensive criteria including A-, D-, E-optimality, prediction error variance (PEV), Cook's distance (CD), and distance-based measures. Features multi-criteria convergence detection, restart mechanisms, rank-based selection with pressure control, adaptive mutation, diversity preservation, and numerically stable matrix operations. Includes convergence diagnostics, configurable optimization windows, and both modern clean interfaces with legacy compatibility functions.

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5.06 score 36 scripts 216 downloads

EMMREML - Fitting Mixed Models with Known Covariance Structures

The main functions are 'emmreml', and 'emmremlMultiKernel'. 'emmreml' solves a mixed model with known covariance structure using the 'EMMA' algorithm. 'emmremlMultiKernel' is a wrapper for 'emmreml' to handle multiple random components with known covariance structures. The function 'emmremlMultivariate' solves a multivariate gaussian mixed model with known covariance structure using the 'ECM' algorithm.

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3.65 score 2 stars 206 scripts 1.1k downloads