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knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE) library(eyeprocess)
partial <- score_partial_response_pattern( calibrated_mirt_model, response_pattern = c(1, 0, 1, NA, NA, NA), method = "MAP" ) stream <- score_response_stream( calibrated_mirt_model, response_pattern = c(1, 0, 1, 1, 0, 1), method = "MAP" ) streaming_score_history(stream) plot(stream)
Streaming scoring is an operational building block. High-stakes deployment still requires calibrated item banks, latency/stopping validation, privacy governance, and score-use rules.
bundle <- collect_validation_evidence( model_spec = spec, recovery = recovery_summary, coverage = coverage_audit, convergence = convergence_audit, ppc = ppc, stress_tests = stress_tests, external_validation = external_results, process_ablation = ablation, negative_controls = negative_controls, preflight = preflight, drift = drift, model_name = "joint_process_model" ) validation_bundle_manifest(bundle) cat(validation_report(bundle), sep = "\n") plot(bundle) export_validation_bundle(bundle, "validation-export")
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