vignette("appac")) covering
usage on PLOT_FID and the method: the multiplicative
forward model, the PCA decomposition into correlated / uncorrelated /
noise components, robust estimation of the common kappa,
the NA-tolerant drift/daily-factor imputation, and the change-point
detectors.get_changepoints() now dates episode level breakpoints with
a deterministic structural-break model (OLS-MOSUM test + BIC-optimal
breakpoints()), dropping the heavy ‘Rbeast’ dependency and
the need for a random seed.get_variance_changepoints(): detects precision
(variance) breakpoints on the noise-energy signal — the second-moment
counterpart of get_changepoints().Synth_data: a compact, fully
synthetic stress-test set with a known ground truth (attached as
attr(., "truth")) — three samples, ten peaks, three
episodes split by two planted level/variance breakpoints, with brown
(AR(1)) heavy-tailed noise at a 1% repeatability — for unit tests and
examples.appac() now imputes missing area cells: peaks with up
to 30% NA are filled by low-rank reconstruction (svdImpute
/ EM) before the fit; whole missing injections (staggered dates) are
handled by the cross-sample reconstruction.appac() validates minimum-size and degenerate input (at
least 3 samples, 2 peaks and 20 injections per sample, and non-constant
areas), failing with an explanatory error instead of a deep numeric
one.show() and print() methods for the
Appac, Compensation and
Correction classes: a compact summary at the console
(print() also lists per-sample goodness-of-fit) instead of
dumping the full object.check_cols() gains a verbose argument
(default FALSE) that reports which column, peak and sample
names were renamed.debias_ct() shows a progress bar during the chi-square
minimisation sweep.?appac-package).First CRAN release.
appac() runs the correction pipeline: it decomposes
per-cylinder peak areas by principal components into a
pressure-correlated component and per-peak drift, estimates the common
pressure-sensitivity coefficient kappa with a
heavy-tail-robust fit on a drift-reduced signal, and removes slow drift
plus a daily factor. Corrects the response of standard, atmosphere-open
detectors (FID, and more weakly TCD).check_cols() validates and canonicalises the input
columns (role-keyed, so the order of the mapping does not matter).debias_ct() refines the per-peak centres by closed-form
chi-square minimisation, for an optional de-biased second pass.goodness_of_fit() reports, per peak, the reduced
chi-square of the corrected areas against a noise-floor estimate.get_changepoints() provides Bayesian episode/breakpoint
detection on the PC2 drift signal (via ‘Rbeast’).plot_area_pressure(), plot_area_date(),
plot_residuals() and plot_area_pressure_fit()
visualise a fitted object (require the suggested ‘ggplot2’ /
‘patchwork’).PLOT_FID: real FID injections from
several control cylinders.