Package index
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cpt_detect() - Unified changepoint detection dispatcher
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cpt_methods() - Introspect available changepoint detection methods
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cpt_penalty() - Construct changepoint penalties
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cpt_cite() - Cite the method behind a result
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new_ggcpt() - Create a ggcpt object
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is_ggcpt() - Test if an object is a ggcpt object
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print(<ggcpt>) - Print a ggcpt object
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cpt_wrapper() - Changepoint wrapper
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ecp_wrapper() - ecp wrapper
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fpop_wrapper() - FPOP wrapper — Functional Pruning Optimal Partitioning
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wbs_wrapper() - WBS wrapper — Wild Binary Segmentation
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wbs2_wrapper() - WBS2 wrapper — Wild Binary Segmentation 2
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not_wrapper() - NOT wrapper — Narrowest-Over-Threshold
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mosum_wrapper() - MOSUM wrapper — Moving Sum
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idetect_wrapper() - Isolate-Detect wrapper
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tguh_wrapper() - TGUH wrapper
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smuce_wrapper() - SMUCE / HSMUCE wrapper — multiscale changepoint inference
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cpop_wrapper() - CPOP wrapper — optimal change-in-slope detection
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cpt_crops()autoplot(<ggcpt_path>)print(<ggcpt_path>)tidy(<ggcpt_path>) - CROPS — the full penalty path of a penalised changepoint method
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bcp_wrapper() - Bayesian changepoint wrapper (Barry-Hartigan product partition model)
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bocpd_wrapper() - Bayesian online changepoint detection wrapper (BOCPD)
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beast_wrapper() - BEAST wrapper — Bayesian estimation of abrupt change, seasonality, and trend
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cpm_wrapper() - Sequential change point model wrapper (CPM)
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kcp_wrapper() - Kernel changepoint wrapper (KCP on running statistics)
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npmojo_wrapper() - Nonparametric MOSUM wrapper (NP-MOJO)
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sn_wrapper() - Self-normalisation wrapper (SNSeg)
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decafs_wrapper() - DeCAFS wrapper — changes amid drift and autocorrelated noise
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envcpt_wrapper() - EnvCpt wrapper — changepoints versus trends versus autocorrelation
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fastcpd_wrapper() - fastcpd wrapper — fast changepoint detection via sequential gradient descent
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inspect_wrapper() - inspect wrapper — high-dimensional changepoints via sparse projection
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ocd_wrapper() - ocd wrapper — online high-dimensional changepoint detection
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geomcp_wrapper() - Geometrically-inspired multivariate changepoint wrapper (geomcp)
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strucchange_wrapper() - Bai-Perron structural break wrapper (strucchange)
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segmented_wrapper() - Broken-line regression wrapper (segmented)
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tidy(<ggcpt>) - Tidy a ggcpt object
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glance(<ggcpt>) - Glance at a ggcpt object
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augment(<ggcpt>) - Augment a ggcpt object
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summary(<ggcpt>)print(<summary.ggcpt>) - Summary of a ggcpt object
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as_tibble(<ggcpt>)as.data.frame(<ggcpt>)format(<ggcpt>)plot(<ggcpt>) - Coerce, format, and plot ggcpt objects
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theme_ggcpt() - ggchangepoint theme
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annotate_segments() - Annotate segments with alternating shading
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autoplot(<ggcpt>) - Autoplot a ggcpt object
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ggcptplot() - Plot for the changepoint package
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ggecpplot() - Plot for the ecp package
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geom_changepoint() - Changepoint vertical rules geom
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geom_cpt_segment() - Changepoint segment level geom
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geom_cpt_ci() - Changepoint confidence interval geom
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stat_changepoint() - Changepoint detection stat
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ggcpt_posterior() - Posterior probability plot for Bayesian results
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ggcpt_runlength() - Run-length posterior heatmap for Bayesian online results
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ggcpt_interactive() - Interactive changepoint plot
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ggcpt_compare() - Compare multiple changepoint detection methods
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ggcpt_compare_table() - Comparison table
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cpt_batch()print(<ggcpt_batch>)tidy(<ggcpt_batch>)autoplot(<ggcpt_batch>) - Batch changepoint detection over many series
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cpt_stability()print(<ggcpt_stability>)autoplot(<ggcpt_stability>) - Changepoint stability diagnostics via bootstrap
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cpt_metrics() - Changepoint accuracy metrics
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cpt_metrics_annotated() - Multi-annotator evaluation
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ggcpt_eval() - Evaluation visualization
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cpt_simulate()rcpt() - Generate simulated changepoint data
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signal_blocks() - Blocks test signal
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signal_fms() - FMS (Four-Metric-Segments) test signal
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signal_mix() - Mix test signal
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signal_teeth() - Teeth test signal
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signal_stairs() - Stairs test signal