R: A Tidy Framework for Changepoint Detection Analysis

# A Tidy Framework for Changepoint Detection Analysis

## Documentation for package ‘tidychangepoint’ version 1.0.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A B C D E F H I L M N P R S T U V W

## -- A --

as.model | Convert, retrieve, or verify a model object
as.model.default | Convert, retrieve, or verify a model object
as.model.tidycpt | Convert, retrieve, or verify a model object
as.segmenter | Convert, retrieve, or verify a segmenter object
as.segmenter.tidycpt | Convert, retrieve, or verify a segmenter object
as.seg_cpt | Convert, retrieve, or verify a segmenter object
as.seg_cpt.breakpointsfull | Convert, retrieve, or verify a segmenter object
as.seg_cpt.cpt | Convert, retrieve, or verify a segmenter object
as.seg_cpt.cptga | Convert, retrieve, or verify a segmenter object
as.seg_cpt.ga | Convert, retrieve, or verify a segmenter object
as.seg_cpt.segmented | Convert, retrieve, or verify a segmenter object
as.seg_cpt.seg_basket | Convert, retrieve, or verify a segmenter object
as.seg_cpt.seg_cpt | Convert, retrieve, or verify a segmenter object
as.seg_cpt.stepmented | Convert, retrieve, or verify a segmenter object
as.seg_cpt.wbs | Convert, retrieve, or verify a segmenter object
as_year | Convert a date into a year

## -- B --

binary2tau | Convert changepoint sets to binary strings
BMDL | Bayesian Maximum Descriptive Length
BMDL.default | Bayesian Maximum Descriptive Length
BMDL.nhpp | Bayesian Maximum Descriptive Length
bogota_pm | Particulate matter in Bogotá, Colombia
build_gabin_population | Initialize populations in genetic algorithms

## -- C --

CET | Hadley Centre Central England Temperature
changepoints | Extract changepoints
changepoints.breakpointsfull | Extract changepoints
changepoints.cpt | Extract changepoints
changepoints.cptga | Extract changepoints
changepoints.default | Extract changepoints
changepoints.ga | Extract changepoints
changepoints.mod_cpt | Extract changepoints
changepoints.segmented | Extract changepoints
changepoints.seg_basket | Extract changepoints
changepoints.seg_cpt | Extract changepoints
changepoints.stepmented | Extract changepoints
changepoints.tidycpt | Extract changepoints
changepoints.wbs | Extract changepoints
compare_algorithms | Compare various models or algorithms for a given changepoint set
compare_models | Compare various models or algorithms for a given changepoint set
cut_by_tau | Use a changepoint set to break a time series into regions

## -- D --

DataCPSim | Simulated time series data
deg_free | Retrieve the degrees of freedom from a 'logLik' object
diagnose | Diagnose the fit of a segmented time series
diagnose.mod_cpt | Diagnose the fit of a segmented time series
diagnose.nhpp | Diagnose the fit of a segmented time series
diagnose.seg_basket | Diagnose the fit of a segmented time series
diagnose.tidycpt | Diagnose the fit of a segmented time series

## -- E --

exceedances | Compute exceedances of a threshold for a time series
exceedances.default | Compute exceedances of a threshold for a time series
exceedances.double | Compute exceedances of a threshold for a time series
exceedances.nhpp | Compute exceedances of a threshold for a time series
exceedances.ts | Compute exceedances of a threshold for a time series

## -- F --

file_name | Obtain a descriptive filename for a tidycpt object
fitness | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.breakpointsfull | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.cpt | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.cptga | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.ga | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.lm | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.seg_basket | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.seg_cpt | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.tidycpt | Retrieve the optimal fitness (or objective function) value used by an algorithm
fitness.wbs | Retrieve the optimal fitness (or objective function) value used by an algorithm
fit_arima | Fit an ARIMA model
fit_lmshift | Regression-based model fitting
fit_lmshift_ar1 | Regression-based model fitting
fit_meanshift | Fast implementation of meanshift model
fit_meanshift_lnorm | Fast implementation of meanshift model
fit_meanshift_norm | Fast implementation of meanshift model
fit_meanshift_norm_ar1 | Fast implementation of meanshift model
fit_meanvar | Fit a model for mean and variance
fit_nhpp | Fit a non-homogeneous Poisson process model to the exceedances of a time series.
fit_trendshift | Regression-based model fitting
fit_trendshift_ar1 | Regression-based model fitting
fun_cpt | Class for model-fitting functions

## -- H --

HQC | Hannan–Quinn information criterion
HQC.default | Hannan–Quinn information criterion
HQC.logLik | Hannan–Quinn information criterion

## -- I --

is_model | Convert, retrieve, or verify a model object
is_segmenter | Convert, retrieve, or verify a segmenter object
is_valid_tau | Pad and unpad changepoint sets with boundary points
italy_grads | Italian University graduates by disciplinary groups from 1926-2013
iweibull | Weibull distribution functions

## -- L --

log_gabin_population | Initialize populations in genetic algorithms
ls_coverage | Algorithmic coverage through tidychangepoint
ls_cpt_penalties | Algorithmic coverage through tidychangepoint
ls_methods | Algorithmic coverage through tidychangepoint
ls_models | Algorithmic coverage through tidychangepoint
ls_penalties | Algorithmic coverage through tidychangepoint
ls_pkgs | Algorithmic coverage through tidychangepoint

## -- M --

MBIC | Modified Bayesian Information Criterion
MBIC.default | Modified Bayesian Information Criterion
MBIC.logLik | Modified Bayesian Information Criterion
mcdf | Cumulative distribution of the exceedances of a time series
mde_rain | Rainfall in Medellín, Colombia
mde_rain_monthly | Rainfall in Medellín, Colombia
MDL | Maximum Descriptive Length
MDL.default | Maximum Descriptive Length
MDL.logLik | Maximum Descriptive Length
mlb_diffs | Differences between leagues in Major League Baseball
model_args | Retrieve the arguments that a model-fitting function used
model_args.breakpointsfull | Retrieve the arguments that a model-fitting function used
model_args.cpt | Retrieve the arguments that a model-fitting function used
model_args.cptga | Retrieve the arguments that a model-fitting function used
model_args.default | Retrieve the arguments that a model-fitting function used
model_args.ga | Retrieve the arguments that a model-fitting function used
model_args.lm | Retrieve the arguments that a model-fitting function used
model_args.seg_cpt | Retrieve the arguments that a model-fitting function used
model_args.wbs | Retrieve the arguments that a model-fitting function used
model_name | Retrieve the name of the model that a segmenter or model used
model_name.breakpointsfull | Retrieve the name of the model that a segmenter or model used
model_name.character | Retrieve the name of the model that a segmenter or model used
model_name.cpt | Retrieve the name of the model that a segmenter or model used
model_name.cptga | Retrieve the name of the model that a segmenter or model used
model_name.default | Retrieve the name of the model that a segmenter or model used
model_name.ga | Retrieve the name of the model that a segmenter or model used
model_name.mod_cpt | Retrieve the name of the model that a segmenter or model used
model_name.segmented | Retrieve the name of the model that a segmenter or model used
model_name.seg_basket | Retrieve the name of the model that a segmenter or model used
model_name.seg_cpt | Retrieve the name of the model that a segmenter or model used
model_name.stepmented | Retrieve the name of the model that a segmenter or model used
model_name.tidycpt | Retrieve the name of the model that a segmenter or model used
model_name.wbs | Retrieve the name of the model that a segmenter or model used
model_variance | Compute model variance
mod_cpt | Base class for changepoint models
mweibull | Weibull distribution functions

## -- N --

new_fun_cpt | Class for model-fitting functions
new_mod_cpt | Base class for changepoint models
new_seg_basket | Default class for candidate changepoint sets
new_seg_cpt | Base class for segmenters

## -- P --

pad_tau | Pad and unpad changepoint sets with boundary points
parameters_weibull | Weibull distribution functions
plot.tidyga | Plot GA information
plot_best_chromosome | Diagnostic plots for 'seg_basket' objects
plot_cpt_repeated | Diagnostic plots for 'seg_basket' objects
plot_intensity | Plot the intensity of an NHPP fit

## -- R --

regions | Extract the regions from a tidycpt object
regions.mod_cpt | Extract the regions from a tidycpt object
regions.tidycpt | Extract the regions from a tidycpt object
regions_tau | Pad and unpad changepoint sets with boundary points
rlnorm_ts_1 | Simulated time series data
rlnorm_ts_2 | Simulated time series data
rlnorm_ts_3 | Simulated time series data

## -- S --

segment | Segment a time series using a variety of algorithms
segment.numeric | Segment a time series using a variety of algorithms
segment.tbl_ts | Segment a time series using a variety of algorithms
segment.ts | Segment a time series using a variety of algorithms
segment.xts | Segment a time series using a variety of algorithms
segment_cptga | Segment a time series using a genetic algorithm
segment_ga | Segment a time series using a genetic algorithm
segment_ga_coen | Segment a time series using a genetic algorithm
segment_ga_random | Segment a time series using a genetic algorithm
segment_ga_shi | Segment a time series using a genetic algorithm
segment_manual | Manually segment a time series
segment_pelt | Segment a time series using the PELT algorithm
seg_basket | Default class for candidate changepoint sets
seg_cpt | Base class for segmenters
seg_params | Retrieve parameters from a segmenter
seg_params.breakpointsfull | Retrieve parameters from a segmenter
seg_params.cpt | Retrieve parameters from a segmenter
seg_params.cptga | Retrieve parameters from a segmenter
seg_params.ga | Retrieve parameters from a segmenter
seg_params.lm | Retrieve parameters from a segmenter
seg_params.seg_cpt | Retrieve parameters from a segmenter
seg_params.wbs | Retrieve parameters from a segmenter
SIC | Schwarz information criterion
split_by_tau | Use a changepoint set to break a time series into regions

## -- T --

tau2binary | Convert changepoint sets to binary strings
tau2time | Convert changepoint sets to time indices
tbl_coef | Format the coefficients from a linear model as a tibble
test_set | Simulate time series with known changepoint sets
tidycpt-class | Container class for 'tidycpt' objects
time2tau | Convert changepoint sets to time indices

## -- U --

unpad_tau | Pad and unpad changepoint sets with boundary points

## -- V --

validate_fun_cpt | Class for model-fitting functions
validate_mod_cpt | Base class for changepoint models
validate_tau | Pad and unpad changepoint sets with boundary points

## -- W --

whomademe | Recover the function that created a model