ggchangepoint - Combines Changepoint Analysis with 'ggplot2'
A unified, tidy, 'ggplot2'-native interface to changepoint
detection in R. A 'cpt_detect()' dispatcher covers fifty
methods (penalised and optimal partitioning, multiscale and
search methods, nonparametric and kernel methods, Bayesian
methods, high-dimensional, functional, covariance and network
methods, regression breaks through a formula interface,
seasonal-trend decomposition and the classical single-change
tests), with distribution families for counts, binary outcomes
and waiting times, missing-value handling, grouped data, and
constraints on locations and segment lengths. Every result is
the same 'ggcpt' object, in one verified location convention,
with 'broom'-style tidy/glance/augment methods, 'autoplot()'
and composable 'ggproto' layers. Around detection: effect
sizes, a test for a change at a date fixed in advance, tests
for a change anywhere, confidence intervals, post-detection
tests, selection of the number of changes, assumption checks
and goodness of fit, robustness to the noise model, stability,
consensus and influence diagnostics, supervised detection,
sequential monitoring, power and study design, benchmarks,
reports and an export under a documented 'JSON' schema. What
each engine does (its runtime, whether its answer survives a
change of units or a reversal of time, its false positives by
noise regime and data type, its false alarms on pure noise) and
the calibration of the package's own intervals and tests are
measured and shipped as data, and 'cpt_recommend()' chooses
from those measurements. 'cpt_register_method()' brings
external and non-CRAN detectors into the same grammar.
