Package: rjd3filters 2.4.0.9000

rjd3filters: Trend-Cycle Extraction with Linear Filters with 'JDemetra+ 3.x'

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 developed in 'JDemetra+' (<https://github.com/jdemetra>), time series analysis software.

Authors:Alain Quartier-la-Tente [aut, cre, cph], Jean Palate [aut], Tanguy Barthelemy [ctb], Anna Smyk [ctb]

rjd3filters_2.4.0.9000.tar.gz
rjd3filters_2.4.0.9000.zip(r-4.7-any)rjd3filters_2.4.0.9000.zip(r-4.6-any)rjd3filters_2.4.0.9000.zip(r-4.5-any)
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rjd3filters_2.4.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
rjd3filters/json (API)

# 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

Pkgdown/docs site:https://rjdverse.github.io

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:
  • retailsa - Seasonally Adjusted Retail Sales

On CRAN:

Conda:

filteringjavajdemetratime-seriestimeseriestrend-cycleopenjdk

5.70 score 3 stars 3 packages 92 scripts 44 exports 8 dependencies

Last updated from:525079e44d. Checks:9 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develOK137
source / vignettesOK202
linux-releaseOK137
macos-releaseOK101
macos-oldrelOK103
windows-develOK102
windows-releaseOK76
windows-oldrelOK94
wasm-releaseOK113

Exports:.jd2r_finitefiltersconfint_filtercpcvcvedf_vardfa_filterdiagnostic_matrixfilterfinite_filtersfstfst_filterget_kernelget_moving_averageget_properties_functionimplicit_forecastsimpute_last_obsis_symmetricis.finite_filtersis.moving_averagelocalpolynomialsloocvelower_boundlp_filtermirrormmsre_filtermoving_averagemseplot_coefplot_gainplot_phasepolynomial_matrixprintrkhs_filterrkhs_kernelrkhs_optimal_bwrkhs_optimization_funrtshowsimple_mato_seasonalunderlying_forecastsupper_boundvar_estimator

Dependencies:backportscheckmateMASSRcpprJavarjd3jarsrjd3toolkitRProtoBuf

Readme and manuals

Help Manual

Help pageTopics
Java Utility Function.jd2r_finitefilters
Confidence intervalsconfint_filter
Compute the degrees of freedom for the variance estimatordf_var
Direct Filter Approachdfa_filter
Compute quality criteria for asymmetric filtersdiagnostic_matrix
Diagnostics and goodness of fit of filtered seriescp cv cve diagnostics-fit loocve rt
Linear Filtering on a Time Seriesfilter
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 Filtersfinite_filters is.finite_filters to_seasonal.finite_filters
FST criteriafst
Estimation of a filter using the Fidelity-Smoothness-Timeliness criteriafst_filter
Get the coefficients of a kernelget_kernel
Get Moving Averages from ARIMA modelget_moving_average
Get properties of filtersget_properties_function
Retrieve implicit forecasts corresponding to the asymmetric filtersimplicit_forecasts
Impute Incomplete Finite Filtersimpute_last_obs
Apply Local Polynomials Filterslocalpolynomials
Local Polynomials Filterslp_filter
Mean Square Revision Error (mmsre) filtermmsre_filter
Manipulation of moving averagescoef.moving_average 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 decompositionmse mse.finite_filters
Plots filters propertiesplot_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 matrixpolynomial_matrix
Print method for Finite Filters Objectsas.matrix.finite_filters print,finite_filters-method show,finite_filters-method
Seasonally Adjusted Retail Salesretailsa
Reproducing Kernel Hilbert Space (RKHS) Filtersrkhs_filter
Get RKHS kernel functionrkhs_kernel
Optimal Bandwidth of Reproducing Kernel Hilbert Space (RKHS) Filtersrkhs_optimal_bw
Optimization Function of Reproducing Kernel Hilbert Space (RKHS) Filtersrkhs_optimization_fun
Simple Moving Averagesimple_ma
Retrieve underlying forecasts corresponding to the asymmetric filtersunderlying_forecasts
Variance Estimatorvar_estimator