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.