inst/doc/uncertainty-calibration.R

In eyeprocess: Harmonize Eye-Tracking, Pupillometry, Biometrics, and Psychometric Process Data

## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>", eval = FALSE)

## -----------------------------------------------------------------------------
# spec <- process_uncertainty_spec(
#   source_sd = c(calibration = 0.018, aoi_assignment = 0.025),
#   draws = 2000
# )
# uncertainty <- estimate_process_uncertainty(
#   trial_features, spec, metrics = c("dwell_ms", "pupil_auc"), cluster = "person_id"
# )
# uncertainty_budget(uncertainty)
# plot_uncertainty_waterfall(uncertainty, metric = "pupil_auc")
# plot_uncertainty_tornado(uncertainty, metric = "pupil_auc")
# propagated <- propagate_process_uncertainty(
#   uncertainty,
#   estimand = function(data) mean(data$pupil_auc, na.rm = TRUE),
#   method = "simulation"
# )

## -----------------------------------------------------------------------------
# drift <- detect_calibration_drift(
#   calibration_samples,
#   window = "30 sec",
#   x_col = "gaze_x",
#   y_col = "gaze_y",
#   time_col = "time"
# )
# plot_calibration_vector_field(drift)
# plot_drift_over_time(drift)
# model <- fit_offline_recalibration(drift, method = "affine", robust = TRUE)
# corrected <- apply_offline_recalibration(samples, model, "gaze_x", "gaze_y")
# audit <- audit_recalibration(calibration_samples, corrected)
# plot_recalibration_before_after(audit)