as.data.frame.wf_quality_report
                        Convert a weighting quality report to a data
                        frame
as.data.frame.wf_variance_result
                        Coerce a variance result to a data frame
as_svrepdesign          Convert WFC replicate weights to a survey
                        replicate design
as_svydesign            Convert WFC weights to a survey design
plot.wf_auto_trim       Plot an automatic trim frontier
plot.wf_blend_result    Plot blend lambda sensitivity
plot.wf_diagnostics     Plot weight diagnostics
plot.wf_propensity_weights
                        Plot propensity overlap and covariate balance
plot.wf_weights         Plot calibrated weight distributions
print.wf_attrition_weights
                        Print attrition weights
print.wf_auto_trim      Print an automatic trim recommendation
print.wf_autoweigh_result
                        Print a guided weighting result
print.wf_blend_result   Print a blend result.
print.wf_cell_merge_plan
                        Print an outcome-blind cell merge plan
print.wf_collapse_plan
                        Print a collapse plan
print.wf_design_data    Print outcome-free survey design data
print.wf_diagnostics    Print diagnostics
print.wf_impact         Print post-lock outcome impact
print.wf_influence      Print influence diagnostics
print.wf_ladder_draft   Print a collapse-ladder draft
print.wf_pipeline       Print a pipeline specification
print.wf_poststrat_plan
                        Print a post-stratification plan
print.wf_precheck       Print a precheck result
print.wf_quality_report
                        Print a weighting quality report
print.wf_replicate_weights
                        Print replicate weights
print.wf_validation     Print a weight-validation result
print.wf_variance_result
                        Print a variance result
print.wf_weight_plan    Print a reviewable weight plan
print.wf_weights        Print calibrated weights
summary.wf_poststrat_plan
                        Summarize a post-stratification plan
wf_apply_collapse       Apply a category collapse plan
wf_approve_plan         Record a human attestation for a reviewed
                        weight plan
wf_assess_impact        Assess descriptive outcome impact after weights
                        are locked
wf_attach_weights       Attach locked weights to analysis data by exact
                        unit ID
wf_attrition            Estimate panel attrition weights
wf_audit_export         Export a self-contained WFC audit file
wf_auto_trim            Recommend a weight-trimming cap
wf_autoweigh            Run a guided workflow from verified design and
                        target objects
wf_blend                Blend online and offline calibrated estimates
wf_calibrate            Calibrate weights from verified design and
                        target objects
wf_collapse_ladder      Declare a post-stratification collapse ladder
wf_compose              Compose multiple weighting stages
wf_diagnose             Diagnose calibrated weights
wf_dims                 Declare calibration dimensions
wf_execute_plan         Execute an approved plan and lock its weights
wf_guided_execute       Execute a guided workflow with an external
                        human approval
wf_guided_plan          Prepare a guided safe weighting workflow
wf_import_reference     Import a verified external reference-sample
                        target
wf_import_target        Import a verified external population target
wf_influence            Diagnose high-influence calibrated units
wf_pipeline             Declare a production weighting pipeline
wf_plan_cells           Plan deterministic, outcome-blind support-cell
                        merging
wf_plan_poststrat       Plan post-stratification cell resolution
wf_plan_weights         Build a reviewable outcome-blind weight plan
wf_poststrat            Post-stratify verified design data to a
                        verified joint target
wf_precheck             Precheck sample and target compatibility
wf_prepare_design       Prepare outcome-free survey design data
wf_propensity           Correct a non-probability sample by
                        inverse-propensity pseudo-weighting.
wf_rake                 Rake verified design data to a verified
                        external target
wf_replicates           Generate re-calibrated replicate weights for
                        variance estimation.
wf_report               Build a weighting quality report
wf_run                  Run a production weighting pipeline
wf_suggest_collapse     Suggest collapse plans from precheck findings
wf_suggest_ladder       Draft a post-stratification collapse ladder
wf_target_population    Target from external population data
wf_target_propensity    Build a propensity target: stacked reference
                        frame and membership model spec.
wf_target_reference     Target from a weighted reference sample
wf_target_template      Create a safe external-target import template
wf_validate             Compare calibrated weights against a reference
                        release
wf_variance             Combine replicate weights and an estimator into
                        a variance and CI.
wfc-tidiers             Broom-style projections for WFC results
wfc_example             Simulated survey weighting example data
