Package: ggchangepoint 0.6.0

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.

Authors:Youzhi Yu [aut, cre]