ria.test 0.3.0

Use D for treatment, C for baseline covariates, and L for post-treatment confounders throughout the implementation, examples, and documentation. The outcome-observation indicator is named observed internally. Rename the matched copy to L-prime and its control to lprime_folds. This is a breaking rename: use lprime_folds in place of zprime_folds. The public arguments trt, pre, and post are unchanged.
L-prime permutations now bypass the LP when every treatment/baseline profile in a fold occurs at least twice. Random cycles within identical profiles give an exact zero-cost optimum without constructing distances or an LP. This also handles all-identical profiles without dividing by zero.
Permutations return indices internally, and L is selected directly instead of multiplying by a dense permutation matrix. Folds with singleton profiles continue to use the full LP; solver status and permutation validity are checked. Folds with fewer than two observations produce an explicit error.
The fast path is reproducible under set.seed(), but chooses tied optima and consumes random numbers differently from earlier versions. Permutations and downstream estimates can therefore change for the same seed.
This bypasses the reported Rsymphony native crash for qualifying folds; it does not fix or diagnose the underlying native defect. The general LP path still depends on Rsymphony and retains its quadratic size.

ria.test 0.2.1

Add torch_seed to ria.test.control() to control Torch neural-network initialization and dropout independently of R’s random-number generator.
Delay Torch device initialization until after R-randomized estimation steps, so first-use Torch initialization cannot change cross-fitting or Z-prime folds.

Restrict estimation to natural effects, randomized interventional analogues, and the TE - TE^R falsification test.
Replace effect with estimand = "test", "natural", or "ria"; the test is now the default.
Align returned estimand names with the paper and remove nuisance fits from the returned object.

Synced fold construction and influence-function identifiers with upstream fixes.