Package: rjd3filters 2.1.1.9000
rjd3filters: Trend-Cycle Extraction with Linear Filters based on JDemetra+ v3.x
This package provides functions to build and apply symmetric and asymmetric moving averages (= linear filters) for trend-cycle extraction. In particular, it implements several modern approaches for real-time estimates from the viewpoint of revisions and time delay in detecting turning points. It includes the local polynomial approach of Proietti and Luati (2008), the Reproducing Kernel Hilbert Space (RKHS) of Dagum and Bianconcini (2008) and the Fidelity-Smoothness-Timeliness approach of Grun-Rehomme, Guggemos, and Ladiray (2018). It is based on Java libraries developped in 'JDemetra+' (<https://github.com/jdemetra>), time series analysis software.
Authors:
rjd3filters_2.1.1.9000.tar.gz
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rjd3filters.pdf |rjd3filters.html✨
rjd3filters/json (API)
NEWS
| # Install 'rjd3filters' in R: |
| install.packages('rjd3filters', repos = c('https://aqlt.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rjdverse/rjd3filters/issues
- retailsa - Seasonally Adjusted Retail Sales
Last updated 1 months agofrom:ab8eb43207. Checks:OK: 5 NOTE: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 15 2024 |
| R-4.5-win | OK | Nov 15 2024 |
| R-4.5-linux | OK | Nov 15 2024 |
| R-4.4-win | NOTE | Nov 15 2024 |
| R-4.4-mac | NOTE | Nov 15 2024 |
| R-4.3-win | OK | Nov 15 2024 |
| R-4.3-mac | OK | Nov 15 2024 |
Exports:.jd2r_finitefiltersconfint_filtercpcross_validationcvcvedfa_filterdiagnostic_matrixfilterfinite_filtersfstfst_filterget_kernelget_moving_averageget_properties_functionimplicit_forecastimpute_last_obsis_symmetricis.finite_filtersis.moving_averagelocalpolynomialsloocvelower_boundlp_filtermirrormmsre_filtermoving_averagemseplot_coefplot_gainplot_phasepolynomial_matrixrkhs_filterrkhs_kernelrkhs_optimal_bwrkhs_optimization_funrtshowsimple_mato_seasonalupper_boundvar_estimator
Dependencies:backportscheckmateMASSRcpprJavarjd3toolkitRProtoBuf
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Confidence intervals | confint_filter |
| Deprecated function | cross_validation deprecated-rjd3filters |
| Direct Filter Approach | dfa_filter |
| Compute quality criteria for asymmetric filters | diagnostic_matrix |
| Diagnostics and goodness of fit of filtered series | cp cv cve diagnostics-fit loocve rt |
| Linear Filtering on a Time Series | filter |
| Operations on Filters | *,ANY,finite_filters-method *,ANY,moving_average-method *,finite_filters,ANY-method *,finite_filters,finite_filters-method *,finite_filters,moving_average-method *,finite_filters,numeric-method *,moving_average,ANY-method *,moving_average,finite_filters-method *,moving_average,moving_average-method *,moving_average,numeric-method *,numeric,moving_average-method +,finite_filters,finite_filters-method +,finite_filters,missing-method +,finite_filters,moving_average-method +,moving_average,finite_filters-method +,moving_average,missing-method +,moving_average,moving_average-method +,moving_average,numeric-method +,numeric,finite_filters-method +,numeric,moving_average-method -,finite_filters,finite_filters-method -,finite_filters,missing-method -,finite_filters,moving_average-method -,finite_filters,numeric-method -,moving_average,finite_filters-method -,moving_average,missing-method -,moving_average,moving_average-method -,moving_average,numeric-method -,numeric,finite_filters-method -,numeric,moving_average-method /,finite_filters,numeric-method /,moving_average,numeric-method cbind.moving_average filters_operations rbind.moving_average sum.moving_average [,finite_filters,ANY-method [,finite_filters,missing-method [,moving_average,logical-method [,moving_average,numeric-method [<-,moving_average,ANY,missing,numeric-method ^,finite_filters,numeric-method ^,moving_average,numeric-method |
| Manipulating Finite Filters | finite_filters is.finite_filters show,finite_filters-method |
| FST criteria | fst |
| Estimation of a filter using the Fidelity-Smoothness-Timeliness criteria | fst_filter |
| Get the coefficients of a kernel | get_kernel |
| Get Moving Averages from ARIMA model | get_moving_average |
| Get properties of filters | get_properties_function |
| Retrieve implicit forecasts corresponding to the asymmetric filters | implicit_forecast |
| Impute Incomplete Finite Filters | impute_last_obs |
| Apply Local Polynomials Filters | localpolynomials |
| Local Polynomials Filters | lp_filter |
| Mean Square Revision Error (mmsre) filter | mmsre_filter |
| Manipulation of moving averages | is.moving_average is_symmetric length.moving_average lower_bound mirror moving_average rev.moving_average show,moving_average-method to_seasonal upper_bound |
| Accuracy/smoothness/timeliness criteria through spectral decomposition | mse |
| Plots filters properties | plot_coef plot_coef.default plot_coef.finite_filters plot_coef.moving_average plot_filters plot_gain plot_gain.finite_filters plot_gain.moving_average plot_phase plot_phase.finite_filters plot_phase.moving_average |
| Create polynomial matrix | polynomial_matrix |
| Seasonally Adjusted Retail Sales | retailsa |
| Reproducing Kernel Hilbert Space (RKHS) Filters | rkhs_filter |
| Get RKHS kernel function | rkhs_kernel |
| Optimal Bandwith of Reproducing Kernel Hilbert Space (RKHS) Filters | rkhs_optimal_bw |
| Optimization Function of Reproducing Kernel Hilbert Space (RKHS) Filters | rkhs_optimization_fun |
| Simple Moving Average | simple_ma |
| Variance Estimator | var_estimator |
