Combines Changepoint Analysis with 'ggplot2'

Documentation for package ‘ggchangepoint’ version 0.7.0

Help Pages

-- A --

alarms	The alarm log of a monitor
alarms.ggcpt_monitor	The alarm log of a monitor
annotate_segments	Annotate segments with alternating shading
as.data.frame.ggcpt	Coerce, format, and plot ggcpt objects
as_cpt_labels	Coerce annotations to changepoint labels
as_cpt_series	Coerce a time series object to values plus a time index
as_ggcpt	Turn external changepoints into a ggcpt result
as_json	Convert a result to JSON
as_json.default	Convert a result to JSON
as_json.ggcpt	Convert a result to JSON
as_tibble.ggcpt	Coerce, format, and plot ggcpt objects
augment.ggcpt	Augment a ggcpt object
autoplot.ggcpt	Autoplot a ggcpt object
autoplot.ggcpt_abruptness	Was the change abrupt? A step against a ramp, at every changepoint
autoplot.ggcpt_attribution	Which coordinates changed? Certified attribution for a multivariate fit
autoplot.ggcpt_batch	Batch changepoint detection over many series
autoplot.ggcpt_benchmark	Benchmark detectors across datasets
autoplot.ggcpt_consensus	Consensus changepoints across several detectors
autoplot.ggcpt_counterfactual	What would have happened without the change? Observed against counterfactual
autoplot.ggcpt_coverage	How often do the confidence intervals cover? A Monte Carlo check
autoplot.ggcpt_delay	Detection delay and false-alarm rate
autoplot.ggcpt_effect	Effect size at each changepoint
autoplot.ggcpt_events	Match detected changepoints to known events
autoplot.ggcpt_influence	Influence diagnostics for a changepoint segmentation
autoplot.ggcpt_k_weights	How sure is the number of changepoints? Weights over K
autoplot.ggcpt_label_curve	Label error as a function of the penalty
autoplot.ggcpt_monitor	A stateful sequential changepoint monitor
autoplot.ggcpt_path	CROPS: the full penalty path of a penalised changepoint method
autoplot.ggcpt_power	Detection power for a changepoint scenario
autoplot.ggcpt_recommendation	Recommend a detection method
autoplot.ggcpt_robustness	Does a changepoint survive a change of noise model?
autoplot.ggcpt_screen	Which of many series changed? Screening with error control across the panel
autoplot.ggcpt_selection	Choose the number of changepoints
autoplot.ggcpt_sensitivity	Sensitivity of a segmentation to its tuning parameters
autoplot.ggcpt_stability	Changepoint stability diagnostics via bootstrap

-- B --

bcp_wrapper	Bayesian changepoint wrapper (Barry-Hartigan product partition model)
beast_wrapper	BEAST wrapper: Bayesian estimation of abrupt change, seasonality, and trend
bfast_wrapper	BFAST wrapper: breaks for additive season and trend
binsegrcpp_wrapper	Fast binary segmentation across loss functions
bocpd_wrapper	Bayesian online changepoint detection wrapper (BOCPD)

-- C --

capa_wrapper	CAPA wrapper: collective and point anomalies (epidemic changepoints)
coef.ggcpt_penalty_model	Learn a penalty from labelled series
cpm_wrapper	Sequential change point model wrapper (CPM)
cpop_wrapper	CPOP wrapper: optimal change-in-slope detection
cpt_abruptness	Was the change abrupt? A step against a ramp, at every changepoint
cpt_annotate_events	Match detected changepoints to known events
cpt_annotations	Per-annotator ground truth for a benchmark dataset
cpt_assumptions	Check the assumptions behind a segmentation
cpt_attribute	Which coordinates changed? Certified attribution for a multivariate fit
cpt_attribute_event	Was a detected change the event you have in mind?
cpt_batch	Batch changepoint detection over many series
cpt_benchmark	Benchmark detectors across datasets
cpt_calibration	What the package promises, against what it delivers
cpt_cite	Cite the method behind a result
cpt_confint	Confidence intervals for changepoint locations
cpt_confint_coverage	How often do the confidence intervals cover? A Monte Carlo check
cpt_consensus	Consensus changepoints across several detectors
cpt_counterfactual	What would have happened without the change? Observed against counterfactual
cpt_crops	CROPS: the full penalty path of a penalised changepoint method
cpt_datasets	A catalogue of benchmark datasets
cpt_data_types	False positives and power by data type
cpt_delay	Detection delay and false-alarm rate
cpt_detect	Unified changepoint detection dispatcher
cpt_effect	Effect size at each changepoint
cpt_export	Write a result to a file, and read it back
cpt_families	Distribution families, and what each request runs
cpt_gof	Goodness of fit, segment by segment
cpt_gt	A publication-ready changepoint table
cpt_import	Write a result to a file, and read it back
cpt_influence	Influence diagnostics for a changepoint segmentation
cpt_install_engines	Install the engines behind a family of methods
cpt_invariances	Invariances of every engine's answer
cpt_k_weights	How sure is the number of changepoints? Weights over K
cpt_labels	Changepoint labels
cpt_label_error	Score a segmentation against labels
cpt_label_error_curve	Label error as a function of the penalty
cpt_learn_penalty	Learn a penalty from labelled series
cpt_leverage	Rank observations by influence
cpt_load_tcpd	Download and cache the Turing Change Point Dataset
cpt_methods	Introspect available changepoint detection methods
cpt_metrics	Changepoint accuracy metrics
cpt_metrics_annotated	Multi-annotator evaluation
cpt_min_detectable	The smallest detectable change
cpt_monitor	A stateful sequential changepoint monitor
cpt_noise_benchmark	False positives and power under four noise regimes
cpt_null_power	What an empty answer could have detected
cpt_null_sizes	False alarms on pure noise at scale
cpt_penalty	Construct changepoint penalties
cpt_power	Detection power for a changepoint scenario
cpt_recommend	Recommend a detection method
cpt_regions	Tidy the significance regions of a ggcpt object
cpt_registered_methods	Register an external changepoint detector
cpt_register_method	Register an external changepoint detector
cpt_replay	Replay a series through a sequential detector
cpt_report	A reproducible report of a changepoint analysis
cpt_robustness	Does a changepoint survive a change of noise model?
cpt_runtimes	Engine runtimes by series length
cpt_scale_space	Scale space: the statistic across bandwidths
cpt_scenarios	A grid of simulation scenarios
cpt_screen	Which of many series changed? Screening with error control across the panel
cpt_segment_models	Fit a model to every segment of a segmentation
cpt_select	Choose the number of changepoints
cpt_sensitivity	Sensitivity of a segmentation to its tuning parameters
cpt_simulate	Generate simulated changepoint data
cpt_solution_path	The solution path of a search-based detector
cpt_stability	Changepoint stability diagnostics via bootstrap
cpt_statistic	The detector's statistic as a function of location
cpt_test	Test detected changepoints
cpt_test_at	Test for a change at a date fixed in advance
cpt_test_null	Test for a change anywhere in a series
cpt_unregister_method	Register an external changepoint detector
cpt_update	Feed observations to a monitor
cpt_verify	Re-run a result against the engines installed now
cpt_wrapper	Changepoint wrapper

-- D --

decafs_wrapper

DeCAFS wrapper: changes amid drift and autocorrelated noise

-- E --

ecp_wrapper	ecp wrapper
envcpt_wrapper	EnvCpt wrapper: changepoints versus trends versus autocorrelation
esac_wrapper	ESAC wrapper: sparsity-adaptive high-dimensional detection

-- F --

fabisearch_wrapper	Network-structure changepoints via non-negative matrix factorisation
fastcpd_wrapper	fastcpd wrapper: fast changepoint detection via sequential gradient descent
fcov_wrapper	Functional covariance changepoints
fmean_wrapper	Functional mean changepoints
format.ggcpt	Coerce, format, and plot ggcpt objects
fpop_wrapper	FPOP wrapper: Functional Pruning Optimal Partitioning

-- G --

GeomChangepoint	ggproto objects for the changepoint layers
GeomCptCi	ggproto objects for the changepoint layers
GeomCptEvent	ggproto objects for the changepoint layers
GeomCptLabel	ggproto objects for the changepoint layers
GeomCptRegion	ggproto objects for the changepoint layers
GeomCptSegment	ggproto objects for the changepoint layers
geomcp_wrapper	Geometrically-inspired multivariate changepoint wrapper (geomcp)
geom_changepoint	Changepoint vertical rules geom
geom_cpt_ci	Changepoint confidence interval geom
geom_cpt_event	Event annotation geom
geom_cpt_label	Changepoint label geom
geom_cpt_region	Significance region geom
geom_cpt_segment	Changepoint segment level geom
ggchangepoint-conditions	Conditions raised by ggchangepoint
ggchangepoint-ggproto	ggproto objects for the changepoint layers
ggchangepoint_error	Conditions raised by ggchangepoint
ggchangepoint_warning	Conditions raised by ggchangepoint
ggcptplot	Plot for the changepoint package
ggcpt_compare	Compare multiple changepoint detection methods
ggcpt_compare_table	Comparison table
ggcpt_eval	Evaluation visualization
ggcpt_interactive	Interactive changepoint plot
ggcpt_methods	Coerce, format, and plot ggcpt objects
ggcpt_plot_methods	Base plot() methods for ggchangepoint result objects
ggcpt_posterior	Posterior probability plot for Bayesian results
ggcpt_runlength	Run-length posterior heatmap for Bayesian online results
ggcpt_scale_space	Scale space: the statistic across bandwidths
ggcpt_solution_path	The solution path of a search-based detector
ggcpt_statistic	The detector's statistic as a function of location
ggecpplot	Plot for the ecp package
glance.ggcpt	Glance at a ggcpt object
glance.ggcpt_attribution	Which coordinates changed? Certified attribution for a multivariate fit
glance.ggcpt_counterfactual	What would have happened without the change? Observed against counterfactual
glance.ggcpt_delay	Detection delay and false-alarm rate
glance.ggcpt_k_weights	How sure is the number of changepoints? Weights over K
glance.ggcpt_screen	Which of many series changed? Screening with error control across the panel
glance.ggcpt_segment_models	Fit a model to every segment of a segmentation

-- H --

hdcov_wrapper	High-dimensional covariance changepoints
hdreg_wrapper	High-dimensional regression changepoints

-- I --

idetect_wrapper	Isolate-Detect wrapper
inspect_wrapper	inspect wrapper: high-dimensional changepoints via sparse projection
is_ggcpt	Test if an object is a ggcpt object

-- K --

kcp_wrapper	Kernel changepoint wrapper (KCP on running statistics)
kwc_wrapper	Robust depth-based changepoints for functional and multivariate data

-- M --

mcp_wrapper	Bayesian formula-based changepoint regression (mcp)
mosum_wrapper	MOSUM wrapper: Moving Sum

-- N --

network_wrapper	Dynamic-network changepoints
new_ggcpt	Create a ggcpt object
not_wrapper	NOT wrapper: Narrowest-Over-Threshold
npmojo_wrapper	Nonparametric MOSUM wrapper (NP-MOJO)
nsp_wrapper	NSP wrapper: Narrowest Significance Pursuit

-- O --

ocd_wrapper

ocd wrapper: online high-dimensional changepoint detection

-- P --

pilliat_wrapper	Pilliat wrapper: high-dimensional detection by three complementary tests
plot.ggcpt	Coerce, format, and plot ggcpt objects
plot.ggcpt_abruptness	Base plot() methods for ggchangepoint result objects
plot.ggcpt_attribution	Base plot() methods for ggchangepoint result objects
plot.ggcpt_batch	Base plot() methods for ggchangepoint result objects
plot.ggcpt_benchmark	Base plot() methods for ggchangepoint result objects
plot.ggcpt_consensus	Base plot() methods for ggchangepoint result objects
plot.ggcpt_counterfactual	Base plot() methods for ggchangepoint result objects
plot.ggcpt_coverage	Base plot() methods for ggchangepoint result objects
plot.ggcpt_delay	Base plot() methods for ggchangepoint result objects
plot.ggcpt_effect	Base plot() methods for ggchangepoint result objects
plot.ggcpt_events	Base plot() methods for ggchangepoint result objects
plot.ggcpt_influence	Base plot() methods for ggchangepoint result objects
plot.ggcpt_k_weights	Base plot() methods for ggchangepoint result objects
plot.ggcpt_label_curve	Base plot() methods for ggchangepoint result objects
plot.ggcpt_monitor	Base plot() methods for ggchangepoint result objects
plot.ggcpt_path	Base plot() methods for ggchangepoint result objects
plot.ggcpt_power	Base plot() methods for ggchangepoint result objects
plot.ggcpt_recommendation	Base plot() methods for ggchangepoint result objects
plot.ggcpt_robustness	Base plot() methods for ggchangepoint result objects
plot.ggcpt_screen	Base plot() methods for ggchangepoint result objects
plot.ggcpt_selection	Base plot() methods for ggchangepoint result objects
plot.ggcpt_sensitivity	Base plot() methods for ggchangepoint result objects
plot.ggcpt_stability	Base plot() methods for ggchangepoint result objects
predict.ggcpt	Forecast from a segment of a segmentation
predict.ggcpt_penalty_model	Learn a penalty from labelled series
print.cpt_label_error	Score a segmentation against labels
print.ggcpt	Print a ggcpt object
print.ggcpt_abruptness	Was the change abrupt? A step against a ramp, at every changepoint
print.ggcpt_assumptions	Check the assumptions behind a segmentation
print.ggcpt_attribution	Which coordinates changed? Certified attribution for a multivariate fit
print.ggcpt_batch	Batch changepoint detection over many series
print.ggcpt_benchmark	Benchmark detectors across datasets
print.ggcpt_consensus	Consensus changepoints across several detectors
print.ggcpt_counterfactual	What would have happened without the change? Observed against counterfactual
print.ggcpt_coverage	How often do the confidence intervals cover? A Monte Carlo check
print.ggcpt_delay	Detection delay and false-alarm rate
print.ggcpt_effect	Effect size at each changepoint
print.ggcpt_events	Match detected changepoints to known events
print.ggcpt_gof	Goodness of fit, segment by segment
print.ggcpt_influence	Influence diagnostics for a changepoint segmentation
print.ggcpt_k_weights	How sure is the number of changepoints? Weights over K
print.ggcpt_label_curve	Label error as a function of the penalty
print.ggcpt_min_detectable	The smallest detectable change
print.ggcpt_monitor	A stateful sequential changepoint monitor
print.ggcpt_null_power	What an empty answer could have detected
print.ggcpt_path	CROPS: the full penalty path of a penalised changepoint method
print.ggcpt_penalty_model	Learn a penalty from labelled series
print.ggcpt_power	Detection power for a changepoint scenario
print.ggcpt_recommendation	Recommend a detection method
print.ggcpt_robustness	Does a changepoint survive a change of noise model?
print.ggcpt_screen	Which of many series changed? Screening with error control across the panel
print.ggcpt_segment_models	Fit a model to every segment of a segmentation
print.ggcpt_selection	Choose the number of changepoints
print.ggcpt_sensitivity	Sensitivity of a segmentation to its tuning parameters
print.ggcpt_stability	Changepoint stability diagnostics via bootstrap
print.ggcpt_test_at	Test for a change at a date fixed in advance
print.ggcpt_verification	Re-run a result against the engines installed now
print.summary.ggcpt	Summary of a ggcpt object

-- R --

rcpt	Generate simulated changepoint data

-- S --

scale_color_cpt	Colour-vision-safe scales for changepoint methods
scale_colour_cpt	Colour-vision-safe scales for changepoint methods
scale_colour_cpt_label	Colour scales for changepoint labels and label errors
scale_fill_cpt	Colour-vision-safe scales for changepoint methods
scale_fill_cpt_label	Colour scales for changepoint labels and label errors
scale_linetype_cpt	Colour-vision-safe scales for changepoint methods
segmented_wrapper	Broken-line regression wrapper (segmented)
signal_blocks	Blocks test signal
signal_fms	FMS (Four-Metric-Segments) test signal
signal_mix	Mix test signal
signal_stairs	Stairs test signal
signal_teeth	Teeth test signal
smuce_wrapper	SMUCE / HSMUCE wrapper: multiscale changepoint inference
sn_wrapper	Self-normalisation wrapper (SNSeg)
StatChangepoint	ggproto objects for the changepoint layers
StatCptRegion	ggproto objects for the changepoint layers
stat_changepoint	Changepoint detection stat
stat_cpt_region	Significance regions computed in the layer
strucchange_wrapper	Bai-Perron structural break wrapper (strucchange)
summary.ggcpt	Summary of a ggcpt object

-- T --

taylor_wrapper	Taylor's change point analyzer
tguh_wrapper	TGUH wrapper
theme_ggcpt	ggchangepoint theme
tidy.cpt_labels	Changepoint labels
tidy.cpt_label_error	Score a segmentation against labels
tidy.ggcpt	Tidy a ggcpt object
tidy.ggcpt_abruptness	Was the change abrupt? A step against a ramp, at every changepoint
tidy.ggcpt_assumptions	Check the assumptions behind a segmentation
tidy.ggcpt_attribution	Which coordinates changed? Certified attribution for a multivariate fit
tidy.ggcpt_batch	Batch changepoint detection over many series
tidy.ggcpt_benchmark	Benchmark detectors across datasets
tidy.ggcpt_counterfactual	What would have happened without the change? Observed against counterfactual
tidy.ggcpt_coverage	How often do the confidence intervals cover? A Monte Carlo check
tidy.ggcpt_delay	Detection delay and false-alarm rate
tidy.ggcpt_effect	Effect size at each changepoint
tidy.ggcpt_events	Match detected changepoints to known events
tidy.ggcpt_gof	Goodness of fit, segment by segment
tidy.ggcpt_influence	Influence diagnostics for a changepoint segmentation
tidy.ggcpt_k_weights	How sure is the number of changepoints? Weights over K
tidy.ggcpt_label_curve	Label error as a function of the penalty
tidy.ggcpt_min_detectable	The smallest detectable change
tidy.ggcpt_monitor	A stateful sequential changepoint monitor
tidy.ggcpt_null_power	What an empty answer could have detected
tidy.ggcpt_path	CROPS: the full penalty path of a penalised changepoint method
tidy.ggcpt_penalty_model	Learn a penalty from labelled series
tidy.ggcpt_power	Detection power for a changepoint scenario
tidy.ggcpt_recommendation	Recommend a detection method
tidy.ggcpt_robustness	Does a changepoint survive a change of noise model?
tidy.ggcpt_screen	Which of many series changed? Screening with error control across the panel
tidy.ggcpt_segment_models	Fit a model to every segment of a segmentation
tidy.ggcpt_selection	Choose the number of changepoints
tidy.ggcpt_sensitivity	Sensitivity of a segmentation to its tuning parameters
tidy.ggcpt_stability	Changepoint stability diagnostics via bootstrap
tidy.ggcpt_test_at	Test for a change at a date fixed in advance
tidy.ggcpt_verification	Re-run a result against the engines installed now
trend_wrapper	Classical single-changepoint tests (Pettitt, Buishand, SNHT)

-- V --

var_wrapper

VAR(1) changepoints

-- W --

wbs2_wrapper	WBS2 wrapper: Wild Binary Segmentation 2
wbsts_wrapper	WBS for nonstationary time series
wbs_wrapper	WBS wrapper: Wild Binary Segmentation