Tidy methods for changepoint analysis | Retrieving information using the broom interface | Other methods | Structure | Segmenters | Models
Package: tidychangepoint 1.0.5
tidychangepoint: A Tidy Framework for Changepoint Detection Analysis
Changepoint detection algorithms for R are widespread but have different interfaces and reporting conventions. This makes the comparative analysis of results difficult. We solve this problem by providing a tidy, unified interface for several different changepoint detection algorithms. We also provide consistent numerical and graphical reporting leveraging the 'broom' and 'ggplot2' packages.
Authors:
tidychangepoint_1.0.5.tar.gz
tidychangepoint_1.0.5.zip(r-4.7)tidychangepoint_1.0.5.zip(r-4.6)tidychangepoint_1.0.5.zip(r-4.5)
tidychangepoint_1.0.5.tgz(r-4.6-any)tidychangepoint_1.0.5.tgz(r-4.5-any)
tidychangepoint_1.0.5.tar.gz(r-4.7-any)tidychangepoint_1.0.5.tar.gz(r-4.6-any)
tidychangepoint_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tidychangepoint/json (API)
| # Install 'tidychangepoint' in R: |
| install.packages('tidychangepoint', repos = c('https://beanumber.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/beanumber/tidychangepoint/issues
Pkgdown/docs site:https://beanumber.github.io
Datasets:
- bogota_pm - Particulate matter in Bogotá, Colombia
- CET - Hadley Centre Central England Temperature
- DataCPSim - Simulated time series data
- italy_grads - Italian University graduates by disciplinary groups from 1926-2013
- mde_rain - Rainfall in Medellín, Colombia
- mde_rain_monthly - Rainfall in Medellín, Colombia
- mlb_diffs - Differences between leagues in Major League Baseball
- rlnorm_ts_1 - Simulated time series data
- rlnorm_ts_2 - Simulated time series data
- rlnorm_ts_3 - Simulated time series data
Last updated from:22e0060633. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 223 | ||
| source / vignettes | OK | 218 | ||
| linux-release-x86_64 | OK | 219 | ||
| macos-release-arm64 | OK | 126 | ||
| macos-oldrel-arm64 | OK | 134 | ||
| windows-devel | OK | 159 | ||
| windows-release | OK | 156 | ||
| windows-oldrel | OK | 162 | ||
| wasm-release | OK | 175 |
Exports:as_yearas.modelas.seg_cptas.segmenteraugmentbinary2tauBMDLbuild_gabin_populationchangepointschromo2taucompare_algorithmscompare_modelscut_by_taudeg_freediagnoseevaluate_cptsevolve_gbmdlexceedancesfile_namefit_arimafit_lmshiftfit_lmshift_ar1fit_meanshiftfit_meanshift_lnormfit_meanshift_normfit_meanshift_norm_ar1fit_meanvarfit_nhppfit_trendshiftfit_trendshift_ar1fitnessfun_cptglanceHQCis_modelis_segmenteris_valid_tauiweibulljunta_1_puntos_cambiojunta_k_puntos_cambiolog_gabin_populationls_coveragels_cpt_penaltiesls_methodsls_modelsls_penaltiesls_pkgsmat_cp_2_listmata_1_tau_voladomata_k_tau_voladoMBICmcdfMDLmod_cptmodel_argsmodel_namemodel_variancemuta_1_cp_BMDLmuta_k_cp_BMDLmweibullnew_fun_cptnew_mod_cptnew_seg_basketnew_seg_cptpad_tauparameters_weibullplot_best_chromosomeplot_cpt_repeatedplot_intensityprobs_vec_MDLregionsregions_tauseg_basketseg_cptseg_paramssegmentsegment_coensegment_cptgasegment_gasegment_ga_coensegment_ga_randomsegment_ga_shisegment_manualsegment_peltselec_k_pares_de_padresSICsim_1_cp_BMDLsim_k_cp_BMDLsplit_by_tautau2binarytau2timetbl_coeftest_settidytime2tauunpad_tauvalidate_fun_cptvalidate_mod_cptvalidate_tauwhomademe
Dependencies:anytimeBHcachemchangepointchangepointGAcliclueclustercodetoolscpp11crayondoParalleldplyrfarverfastmapforeachGAgenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclelubridatemagrittrMASSmemoisenlmepillarpkgconfigprettyunitspurrrR6RColorBrewerRcppRcppArmadillorlangS7sandwichscalessegmentedstringistringrstrucchangetibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewbswithrxtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convert a date into a year | as_year |
| Convert, retrieve, or verify a model object | as.model as.model.default as.model.tidycpt is_model |
| Convert, retrieve, or verify a segmenter object | as.segmenter as.segmenter.tidycpt as.seg_cpt as.seg_cpt.breakpointsfull as.seg_cpt.cpt as.seg_cpt.cptga as.seg_cpt.ga as.seg_cpt.segmented as.seg_cpt.seg_basket as.seg_cpt.seg_cpt as.seg_cpt.stepmented as.seg_cpt.wbs is_segmenter |
| Convert changepoint sets to binary strings | binary2tau tau2binary |
| Bayesian Maximum Descriptive Length | BMDL BMDL.default BMDL.nhpp |
| Particulate matter in Bogotá, Colombia | bogota_pm |
| Initialize populations in genetic algorithms | build_gabin_population log_gabin_population |
| Hadley Centre Central England Temperature | CET |
| Extract changepoints | changepoints changepoints.breakpointsfull changepoints.cpt changepoints.cptga changepoints.default changepoints.ga changepoints.mod_cpt changepoints.segmented changepoints.seg_basket changepoints.seg_cpt changepoints.stepmented changepoints.tidycpt changepoints.wbs |
| Compare various models or algorithms for a given changepoint set | compare_algorithms compare_models |
| Use a changepoint set to break a time series into regions | cut_by_tau split_by_tau |
| Simulated time series data | DataCPSim rlnorm_ts_1 rlnorm_ts_2 rlnorm_ts_3 |
| Retrieve the degrees of freedom from a 'logLik' object | deg_free |
| Diagnose the fit of a segmented time series | diagnose diagnose.mod_cpt diagnose.nhpp diagnose.seg_basket diagnose.tidycpt |
| Compute exceedances of a threshold for a time series | exceedances exceedances.default exceedances.double exceedances.nhpp exceedances.ts |
| Obtain a descriptive filename for a tidycpt object | file_name |
| Fit an ARIMA model | fit_arima |
| Regression-based model fitting | fit_lmshift fit_lmshift_ar1 fit_trendshift fit_trendshift_ar1 |
| Fast implementation of meanshift model | fit_meanshift fit_meanshift_lnorm fit_meanshift_norm fit_meanshift_norm_ar1 |
| Fit a model for mean and variance | fit_meanvar |
| Fit a non-homogeneous Poisson process model to the exceedances of a time series. | fit_nhpp |
| Retrieve the optimal fitness (or objective function) value used by an algorithm | fitness fitness.breakpointsfull fitness.cpt fitness.cptga fitness.ga fitness.lm fitness.seg_basket fitness.seg_cpt fitness.tidycpt fitness.wbs |
| Hannan–Quinn information criterion | HQC HQC.default HQC.logLik |
| Italian University graduates by disciplinary groups from 1926-2013 | italy_grads |
| Weibull distribution functions | iweibull mweibull parameters_weibull |
| Algorithmic coverage through tidychangepoint | ls_coverage ls_cpt_penalties ls_methods ls_models ls_penalties ls_pkgs |
| Modified Bayesian Information Criterion | MBIC MBIC.default MBIC.logLik |
| Cumulative distribution of the exceedances of a time series | mcdf |
| Rainfall in Medellín, Colombia | mde_rain mde_rain_monthly |
| Maximum Descriptive Length | MDL MDL.default MDL.logLik |
| Differences between leagues in Major League Baseball | mlb_diffs |
| Retrieve the arguments that a model-fitting function used | model_args model_args.breakpointsfull model_args.cpt model_args.cptga model_args.default model_args.ga model_args.lm model_args.seg_cpt model_args.wbs |
| Retrieve the name of the model that a segmenter or model used | model_name model_name.breakpointsfull model_name.character model_name.cpt model_name.cptga model_name.default model_name.ga model_name.mod_cpt model_name.segmented model_name.seg_basket model_name.seg_cpt model_name.stepmented model_name.tidycpt model_name.wbs |
| Compute model variance | model_variance |
| Class for model-fitting functions | fun_cpt new_fun_cpt validate_fun_cpt |
| Base class for changepoint models | mod_cpt new_mod_cpt validate_mod_cpt |
| Default class for candidate changepoint sets | new_seg_basket seg_basket |
| Base class for segmenters | new_seg_cpt seg_cpt |
| Pad and unpad changepoint sets with boundary points | is_valid_tau pad_tau regions_tau unpad_tau validate_tau |
| Diagnostic plots for 'seg_basket' objects | plot_best_chromosome plot_cpt_repeated |
| Plot the intensity of an NHPP fit | plot_intensity |
| Plot GA information | plot.tidyga |
| Extract the regions from a tidycpt object | regions regions.mod_cpt regions.tidycpt |
| Retrieve parameters from a segmenter | seg_params seg_params.breakpointsfull seg_params.cpt seg_params.cptga seg_params.ga seg_params.lm seg_params.seg_cpt seg_params.wbs |
| Segment a time series using a variety of algorithms | segment segment.numeric segment.tbl_ts segment.ts segment.xts |
| Segment a time series using a genetic algorithm | segment_cptga |
| Segment a time series using a genetic algorithm | segment_ga segment_ga_coen segment_ga_random segment_ga_shi |
| Manually segment a time series | segment_manual |
| Segment a time series using the PELT algorithm | segment_pelt |
| Schwarz information criterion | SIC |
| Convert changepoint sets to time indices | tau2time time2tau |
| Format the coefficients from a linear model as a tibble | tbl_coef |
| Simulate time series with known changepoint sets | test_set |
| Container class for 'tidycpt' objects | tidycpt-class |
| Recover the function that created a model | whomademe |
