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Calibration uncertainty and eye-tracking data quality

Version 0.9 makes measurement quality visible in the analysis object. Calibration/validation error, successive-sample precision, effective sampling frequency, irregular sampling, and data loss can be summarized rather than hidden in preprocessing.

cal <- read.csv(system.file("extdata","calibration_targets_demo.csv", package="eyeprocess"))
m <- calibration_error_model(cal)
gaze_uncertainty_ellipse(m)
plot(m)

g <- read.csv(system.file("extdata","gaze_quality_demo.csv", package="eyeprocess"))
q <- gaze_data_quality_profile(g, valid="valid", by="person_id")
data_quality_reporting_table(q)

propagate_calibration_uncertainty() and probabilistic_aoi_assignment() propagate empirical calibration error into AOI membership. These probabilities concern spatial membership under the error model; they are not probabilities of psychological attention.

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.