Changelog

Source: NEWS.md

sondage 0.8

Initial CRAN release.

Sampling

Five dispatchers, 13 built-in methods:

• equal_prob_wor(N, n, method=): "srs", "systematic", "bernoulli".
• equal_prob_wr(N, n, method=): "srs".
• unequal_prob_wor(pik, method=): "cps" (conditional Poisson / maximum entropy), "brewer", "systematic", "poisson", "sps" (sequential Poisson), "pareto".
• unequal_prob_wr(hits, method=): "chromy" (minimum replacement), "multinomial".
• balanced_wor(pik, aux, strata, method=): "cube" with optional stratification.

All sampling functions return S3 design objects with class c(prob_class, wor_or_wr, "sondage_sample") (cube designs additionally carry "balanced").

Design queries

• inclusion_prob(): first-order inclusion probabilities (from size measures, or extracted from a WOR design).
• expected_hits(): expected number of selections (WR analogue).
• joint_inclusion_prob(): exact for cps, systematic, poisson, srs, bernoulli; high-entropy approximation for brewer, sps, pareto, cube.
• joint_expected_hits(): exact analytic for multinomial / srs, simulation-based for chromy.
• sampling_cov(): sampling covariance; weighted = TRUE returns Sen-Yates-Grundy check quantities.

All generics accept sampled_only = TRUE to return only the sampled-units submatrix (useful for large populations).

Extensibility

• register_method() / unregister_method() / registered_methods() / is_registered_method() / method_spec() register custom unequal-probability methods that flow through the existing dispatchers and generics.
• he_jip() (Brewer & Donadio 2003 high-entropy approximation) and hajek_jip() (Hajek 1964) are exported and can be passed directly as joint_fn to register_method().

Other features

• Batch sampling via nrep for Monte Carlo simulations. Fixed-size designs return a matrix; random-size designs return a list.
• Permanent random numbers (prn) for sample coordination (Bernoulli, Poisson, SPS, Pareto).
• C implementations for all sampling algorithms.
• Vignette “Extending sondage with Custom Methods”.