Package: rjd3toolkit 3.3.1
rjd3toolkit: Utility Functions around 'JDemetra+ 3.0'
R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It provides functions allowing to model time series (create outlier regressors, user-defined calendar regressors, UCARIMA models...), to test the presence of trading days or seasonal effects and also to set specifications in pre-adjustment and benchmarking when using rjd3x13 or rjd3tramoseats.
Authors:
rjd3toolkit_3.3.1.tar.gz
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rjd3toolkit.pdf |rjd3toolkit.html✨
rjd3toolkit/json (API)
NEWS
# Install 'rjd3toolkit' in R: |
install.packages('rjd3toolkit', repos = c('https://aqlt.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rjdverse/rjd3toolkit/issues
jdemetraseasonal-adjustmenttimeseries
Last updated 1 days agofrom:3bc96ad3ef. Checks:OK: 5 NOTE: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 28 2024 |
R-4.5-win | OK | Oct 28 2024 |
R-4.5-linux | OK | Oct 28 2024 |
R-4.4-win | NOTE | Oct 28 2024 |
R-4.4-mac | NOTE | Oct 28 2024 |
R-4.3-win | OK | Oct 28 2024 |
R-4.3-mac | OK | Oct 28 2024 |
Exports:.enum_extract.enum_of.enum_sextract.enum_sof.jd2p_calendars.jd2p_context.jd2p_variables.jd2r_calendars.jd2r_lts.jd2r_matrix.jd2r_modellingcontext.jd2r_mts.jd2r_ts.jd2r_tscollection.jd2r_tsdata.jd2r_ucarima.jd2r_variables.jd3_object.jdomain.likelihood.p2jd_calendar.p2jd_calendars.p2jd_context.p2jd_variables.p2r_arima.p2r_calendars.p2r_context.p2r_datasupplier.p2r_datasuppliers.p2r_date.p2r_iv.p2r_ivs.p2r_likelihood.p2r_matrix.p2r_metadata.p2r_moniker.p2r_outliers.p2r_parameter.p2r_parameters.p2r_parameters_estimation.p2r_parameters_rslt.p2r_parameters_rsltx.p2r_ramps.p2r_regarima_rslts.p2r_sa_decomposition.p2r_sa_diagnostics.p2r_sequences.p2r_span.p2r_spec_benchmarking.p2r_spec_sarima.p2r_test.p2r_ts.p2r_tscollection.p2r_tsdata.p2r_ucarima.p2r_uservars.p2r_variables.proc_bool.proc_data.proc_desc.proc_dictionary.proc_dictionary2.proc_int.proc_likelihood.proc_matrix.proc_numeric.proc_parameter.proc_parameters.proc_str.proc_test.proc_ts.proc_vector.r2jd_calendars.r2jd_make_ts.r2jd_make_tscollection.r2jd_matrix.r2jd_modellingcontext.r2jd_sarima.r2jd_tmp_ts.r2jd_ts.r2jd_tscollection.r2jd_tsdata.r2jd_tsdomain.r2jd_variables.r2p_calendar.r2p_calendars.r2p_context.r2p_datasupplier.r2p_datasuppliers.r2p_date.r2p_iv.r2p_ivs.r2p_lparameters.r2p_metadata.r2p_moniker.r2p_outliers.r2p_parameter.r2p_parameters.r2p_ramps.r2p_sequences.r2p_span.r2p_spec_benchmarking.r2p_spec_sarima.r2p_ts.r2p_tscollection.r2p_tsdata.r2p_uservars.tsmonikeradd_outlieradd_rampadd_usrdefvaraggregateao_variablearima_differencearima_modelarima_propertiesarima_sumautocorrelationsautocorrelations_inverseautocorrelations_partialbowmanshentoncalendar_tdcdf_chi2cdf_gammacdf_inverse_gammacdf_inverse_gaussiancdf_tchained_calendarclean_extremitiescompare_annual_totalsdata_to_tsDATE_MAXDATE_MINdaysOfdensity_chi2density_gammadensity_inverse_gammadensity_inverse_gaussiandensity_tdiagnosticsdictionarydifferencesdifferencing_fastdo_stationarydoornikhanseneaster_dateseaster_dayeaster_variablefixed_dayfixed_week_dayholidaysintervention_variablejarqueberajulianeaster_variablekurtosisljungboxlong_term_meanlp_variablels_variablemadmodelling_contextnational_calendarperiodic_splinesperiodic.contrastsperiodic.dummiesr2jd_calendartsramp_variablerandom_chi2random_gammarandom_inverse_gammarandom_inverse_gaussianrandom_trangemean_tstatreload_dictionariesremove_outlierremove_rampresultsa_decompositionsa_preprocessingsa.decompositionsadecompositionsarima_decomposesarima_estimatesarima_hannan_rissanensarima_modelsarima_propertiessarima_randomseasonality_canovahansenseasonality_canovahansen_trigsseasonality_combinedseasonality_fseasonality_friedmanseasonality_kruskalwallisseasonality_modified_qsseasonality_periodogramseasonality_qsset_arimaset_automodelset_basicset_benchmarkingset_easterset_estimateset_outlierset_tradingdaysset_transformsingle_dayskewnessso_variablespecial_daystatisticalteststock_tdtc_variabletdtd_canovahansentd_ftd_timevaryingtestofrunstestofupdownrunsto_tsto_tscollectiontrigonometric_variablests_adjustts_interpolatetsdata_ofucarima_canonicalucarima_estimateucarima_modelucarima_wkuser_definedweighted_calendar
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Information on the (log-)likelihood | .likelihood |
Java Utility Functions | .enum_extract .enum_of .enum_sextract .enum_sof .jd2p_calendars .jd2p_context .jd2p_variables .jd2r_calendars .jd2r_lts .jd2r_matrix .jd2r_modellingcontext .jd2r_mts .jd2r_ts .jd2r_tscollection .jd2r_tsdata .jd2r_ucarima .jd2r_variables .jd3_object .jdomain .p2jd_calendar .p2jd_calendars .p2jd_context .p2jd_variables .p2r_arima .p2r_calendars .p2r_context .p2r_datasupplier .p2r_datasuppliers .p2r_date .p2r_iv .p2r_ivs .p2r_likelihood .p2r_matrix .p2r_metadata .p2r_moniker .p2r_outliers .p2r_parameter .p2r_parameters .p2r_parameters_estimation .p2r_parameters_rslt .p2r_parameters_rsltx .p2r_ramps .p2r_regarima_rslts .p2r_sa_decomposition .p2r_sa_diagnostics .p2r_sequences .p2r_span .p2r_spec_benchmarking .p2r_spec_sarima .p2r_test .p2r_ts .p2r_tscollection .p2r_tsdata .p2r_ucarima .p2r_uservars .p2r_variables .proc_bool .proc_data .proc_desc .proc_dictionary .proc_dictionary2 .proc_int .proc_likelihood .proc_matrix .proc_numeric .proc_parameter .proc_parameters .proc_str .proc_test .proc_ts .proc_vector .r2jd_calendars .r2jd_make_ts .r2jd_make_tscollection .r2jd_matrix .r2jd_modellingcontext .r2jd_sarima .r2jd_tmp_ts .r2jd_ts .r2jd_tscollection .r2jd_tsdata .r2jd_tsdomain .r2jd_variables .r2p_calendar .r2p_calendars .r2p_context .r2p_datasupplier .r2p_datasuppliers .r2p_date .r2p_iv .r2p_ivs .r2p_lparameters .r2p_metadata .r2p_moniker .r2p_outliers .r2p_parameter .r2p_parameters .r2p_ramps .r2p_sequences .r2p_span .r2p_spec_benchmarking .r2p_spec_sarima .r2p_ts .r2p_tscollection .r2p_tsdata .r2p_uservars DATE_MAX DATE_MIN jd3_utilities |
Title | .tsmoniker |
Retail trade statistics in Australia | ABS |
Manage Outliers/Ramps in Specification | add_outlier add_ramp remove_outlier remove_ramp |
Add a User-Defined Variable to Pre-Processing Specification. | add_usrdefvar |
Aggregation of time series | aggregate |
Remove an arima model from an existing one. More exactly, m_diff = m_left - m_right iff m_left = m_right + m_diff. | arima_difference |
ARIMA Model | arima_model |
Properties of an ARIMA model; the (pseudo-)spectrum and the auto-covariances of the model are returned | arima_properties |
Sum ARIMA Models | arima_sum |
Autocorrelation Functions | autocorrelations autocorrelations_inverse autocorrelations_partial |
Trading day regressors with pre-defined holidays | calendar_td |
Create a Chained Calendar | chained_calendar |
Removal of missing values at the beginning/end | clean_extremities |
Compare the annual totals of two series (usually the raw series and the seasonally adjusted series) | compare_annual_totals |
Promote a R time series to a "full" 'ts' of JDemetra+ | data_to_ts |
Provides a list of dates corresponding to each period of the given time series | daysOf |
The Chi-Squared Distribution | cdf_chi2 chi2distribution density_chi2 random_chi2 |
The Gamma Distribution | cdf_gamma density_gamma gammadistribution random_gamma |
The Inverse-Gamma Distribution | cdf_inverse_gamma density_inverse_gamma invgammadistribution random_inverse_gamma |
The Inverse-Gaussian Distribution | cdf_inverse_gaussian density_inverse_gaussian invgaussiandistribution random_inverse_gaussian |
The Student Distribution | cdf_t density_t random_t studentdistribution |
Deprecated functions | deprecated-rjd3toolkit sa.decomposition |
Generic Diagnostics Function | diagnostics diagnostics.JD3 |
Get Dictionary and Result | dictionary result user_defined |
Differencing of a series | differences |
Automatic differencing | differencing_fast |
Automatic stationary transformation | do_stationary |
Display Easter Sunday dates in given period | easter_dates |
Set a Holiday on an Easter related day | easter_day |
Easter regressor | easter_variable julianeaster_variable |
Belgian exports to European countries | Exports |
Set a holiday on a Fixed Day | fixed_day |
Set a Holiday on a Fixed Week Day | fixed_week_day |
Daily calendar regressors corresponding to holidays | holidays |
Belgian imports from European countries | Imports |
Intervention variable | intervention_variable |
JD3 print functions | jd3_print print.JD3_ARIMA print.JD3_LIKELIHOOD print.JD3_REGARIMA_RSLTS print.JD3_SARIMA print.JD3_SARIMA_ESTIMATION print.JD3_SPAN print.JD3_UCARIMA |
Ljung-Box Test | ljungbox |
Display Long-term means for a set of calendar regressors | long_term_mean |
Leap Year regressor | lp_variable |
Compute a robust median absolute deviation (MAD) | mad |
Create context | modelling_context |
Create a National Calendar | national_calendar |
Normality Tests | bowmanshenton doornikhansen jarquebera kurtosis normality_tests skewness |
Generating Outlier regressors | ao_variable ls_variable outliers_variables so_variable tc_variable |
Period splines | periodic_splines |
Periodic dummies and contrasts | periodic.contrasts periodic.dummies |
Calendars Print Methods | print.calendars print.JD3_CALENDAR print.JD3_EASTERDAY print.JD3_FIXEDDAY print.JD3_FIXEDWEEKDAY print.JD3_SINGLEDAY print.JD3_SPECIALDAY |
Create Java CalendarTimeSeries | r2jd_calendarts |
Ramp regressor | ramp_variable |
Range-Mean Regression | rangemean_tstat |
Title | reload_dictionaries |
US Retail trade statistics | retail |
Runs Tests around the mean or the median | runstests testofruns testofupdownruns |
Generic Preprocessing Function | sa_preprocessing |
Generic Function for Seasonal Adjustment Decomposition | plot.JD3_SADECOMPOSITION print.JD3_SADECOMPOSITION sadecomposition sa_decomposition |
Decompose SARIMA Model into three components trend, seasonal, irregular | sarima_decompose |
Estimate SARIMA Model | sarima_estimate |
Title | sarima_hannan_rissanen |
Seasonal ARIMA model (Box-Jenkins) | sarima_model |
SARIMA Properties | sarima_properties |
Simulate Seasonal ARIMA | sarima_random |
Canova-Hansen seasonality test | seasonality_canovahansen |
Canova-Hansen test using trigonometric variables | seasonality_canovahansen_trigs |
"X12" Test On Seasonality | seasonality_combined |
F-test on seasonal dummies | seasonality_f |
Friedman Seasonality Test | seasonality_friedman |
Kruskall-Wallis Seasonality Test | seasonality_kruskalwallis |
Modified QS Seasonality Test (Maravall) | seasonality_modified_qs |
Periodogram Seasonality Test | seasonality_periodogram |
QS (seasonal Ljung-Box) test. | seasonality_qs |
Set ARIMA Model Structure in Pre-Processing Specification | set_arima |
Set Arima Model Identification in Pre-Processing Specification | set_automodel |
Set estimation sub-span and quality check specification | set_basic |
Set Benchmarking Specification | set_benchmarking |
Set Easter effect correction in Pre-Processing Specification | set_easter |
Set Numeric Estimation Parameters and Modelling Span | set_estimate |
Set Outlier Detection Parameters | set_outlier |
Set Calendar effects correction in Pre-Processing Specification | set_tradingdays |
Set Log-level Transformation and Decomposition scheme in Pre-Processing Specification | set_transform |
Set a holiday on a Single Day | single_day |
List of Pre-Defined Holidays to choose from | special_day |
Generic Function For 'JDemetra+' Tests | print.JD3_TEST statisticaltest |
Trading day Regressor for Stock series | stock_td |
Trading day regressors without holidays | td |
Canova-Hansen test for stable trading days | td_canovahansen |
Residual Trading Days Test | td_f |
Likelihood ratio test on time varying trading days | td_timevarying |
Creates a time series object | to_ts |
Creates a collection of time series | to_tscollection |
Trigonometric variables | trigonometric_variables |
Multiplicative adjustment of a time series for leap year / length of periods | ts_adjust |
Interpolation of a time series with missing values | ts_interpolate |
Title | tsdata_of |
Makes a UCARIMA model canonical; more specifically, put all the noise of the components in one dedicated component | ucarima_canonical |
Estimate UCARIMA Model | ucarima_estimate |
Creates an UCARIMA model, which is composed of ARIMA models with independent innovations. | ucarima_model |
Wiener Kolmogorov Estimators | ucarima_wk |
Create a Composite Calendar | weighted_calendar |