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Addressed CRAN feedback by replacing the non-executable fitting
example with a guarded \donttest{} example, enforcing a
two-core ceiling, requiring explicit report-output paths, using
temporary paths in vignettes, and removing direct modification of the
global environment.
Prepared the first CRAN submission candidate.
Added Zenodo DOI documentation and current release-status wording.
Added explicit copyright-holder metadata for the initial CRAN submission.
gp3bayes package scaffold.create_model_contract() for the two approved
initial model families with neutral column mappings and explicit
methodological specifications.gp3bayes_model_contract print method
and deterministic validation tests.audit_model_readiness() for backend-independent
assessment of outcome validity, declared columns, missingness, repeated
measurements, item and trial structure, predictors, interactions, time
terms, and requested participant-level random slopes.gp3bayes_readiness_audit results with
explicit pass, warning, and failure statuses and a concise print
method.build_model_formula() for deterministic,
backend-independent construction of approved fixed-effects, interaction,
participant, item, time, and optional participant-level random-slope
structures.create_prior_specification() and
validate_prior_specification() for explicit binary-logit
and lognormal-duration prior records without creating executable backend
objects.create_model_specification() to combine a model
contract, successful readiness audit, approved formula, and validated
priors into one inspectable backend-independent specification.simulate_hierarchical_binary_data() for
deterministic hierarchical Bernoulli-logit simulation with participant
effects, optional crossed item effects, optional participant condition
slopes, controlled imbalance, and a stored true-parameter record.prepare_hierarchical_binary_data() for explicit
binary-outcome mapping, condition coding, recorded predictor scaling,
missing-data decisions, readiness auditing, and fixed-effects matrix
construction.specify_binary_model() to combine prepared data
with the approved binary contract, restricted hierarchical formula, and
validated backend-independent prior specification.check_binary_prior_predictive() for deterministic
simulation of family-specific prior predictions and structured
plausibility checks without fitting a model or requiring a Bayesian
backend.CITATION.cff and inst/CITATION.brms Bernoulli-logit formulas and
priors.brms
and rstan sampling route without unrestricted formulas or
backend arguments.brms translation, and full MCMC fitting through
rstan.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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