Two interchangeable implementation backends, one modeling
contract
The approved full-MCMC interface remains brms with
either rstan or cmdstanr. Backend portability
should preserve the model family, formula, priors, estimand and sampling
contract. It should not imply identical random-number
streams or identical posterior draws.
backend_capabilities()
#> <gp3bayes_backend_capabilities_v2>
#> backend brms_available backend_package_available backend_package_version
#> rstan TRUE TRUE 2.32.7
#> cmdstanr TRUE TRUE 0.9.0
#> external_runtime_available external_runtime_version
#> TRUE <NA>
#> TRUE 2.39.0
#> ready_for_package_interface algorithm
#> TRUE sampling
#> TRUE sampling
#> model_family_scope
#> Bernoulli-logit and positive uncensored lognormal duration
#> Bernoulli-logit and positive uncensored lognormal duration
#> unrestricted_modeling
#> FALSE
#> FALSE
validate_backend_environment("rstan")
#> <gp3bayes_backend_environment>
#> Backend: rstan
#> Status: ready
#> Compiler smoke test requested: FALSE
#> check status detail
#> brms_package pass 2.23.0
#> backend_package pass 2.32.7
#> external_runtime pass managed by rstan package/toolchain
#> compiler_smoke_test not_assessed not requested
validate_backend_environment("cmdstanr")
#> <gp3bayes_backend_environment>
#> Backend: cmdstanr
#> Status: ready
#> Compiler smoke test requested: FALSE
#> check status detail
#> brms_package pass 2.23.0
#> backend_package pass 0.9.0
#> external_runtime pass 2.39.0
#> compiler_smoke_test not_assessed not requested
An optional compiler smoke test can be requested explicitly and is
not run in this vignette:
validate_backend_environment("rstan", compile_test = TRUE)
validate_backend_environment("cmdstanr", compile_test = TRUE)
Posterior-summary parity
Parity is evaluated relative to Monte Carlo uncertainty rather than
exact draw identity. The data-frame interface below makes the rule
transparent and is also useful for archived summary comparisons.
rstan_summary <- data.frame(
variable = c("b_Intercept", "b_conditiontreatment"),
mean = c(-0.60, 0.40),
sd = c(0.20, 0.15),
mcse_mean = c(0.01, 0.01)
)
cmdstanr_summary <- data.frame(
variable = c("b_Intercept", "b_conditiontreatment"),
mean = c(-0.59, 0.41),
sd = c(0.21, 0.15),
mcse_mean = c(0.01, 0.01)
)
parity <- audit_backend_parity(
rstan_summary,
cmdstanr_summary
)
parity
#> <gp3bayes_backend_parity_audit>
#> Status: pass
#> Parameters compared: 2
#> Review parameters: 0
#> Identical draws expected: FALSE
plot(parity)
With real fits, the same function obtains posterior summaries from
each fit:
parity <- audit_backend_parity(
fit_rstan,
fit_cmdstanr,
variables = c("b_Intercept", "b_conditiontreatment")
)
Object-schema compatibility
A stable release also needs to know when serialized object structure
changes. Schema capture records structure rather than values.
contract <- create_model_contract(
"binary", "selected", "participant_id",
condition_col = "condition"
)
schema <- capture_gp3bayes_schema(contract)
schema
#> <gp3bayes_object_schema>
#> Object class: gp3bayes_model_contract
#> Recorded nodes: 41
#> Maximum depth: 3
#> Values recorded: FALSE
validation <- validate_gp3bayes_schema(contract, schema)
validation
#> <gp3bayes_schema_validation>
#> Status: pass
#> Schema compatibility only: TRUE
Freezing does not write anything unless a path is explicitly
provided:
frozen_schema <- freeze_gp3bayes_schema(schema)
schema_file <- tempfile(fileext = ".rds")
freeze_gp3bayes_schema(frozen_schema, schema_file)
read_gp3bayes_schema(schema_file)
#> <gp3bayes_object_schema>
#> Object class: gp3bayes_model_contract
#> Recorded nodes: 41
#> Maximum depth: 3
#> Values recorded: FALSE
unlink(schema_file)
A schema match is a compatibility check only. It says nothing about
numerical identity, statistical adequacy, or scientific validity.