Package: deseats 1.1.0

deseats: Data-Driven Locally Weighted Regression for Trend and Seasonality in TS

Various methods for the identification of trend and seasonal components in time series (TS) are provided. Among them is a data-driven locally weighted regression approach with automatically selected bandwidth for equidistant short-memory time series. The approach is a combination / extension of the algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y., Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief description of this new method is provided in the package documentation. Furthermore, the package allows its users to apply the base model of the Berlin procedure, version 4.1, as described in Speth (2004) <https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=publicationFile>. Permission to include this procedure was kindly provided by the Federal Statistical Office of Germany.

Authors:Yuanhua Feng [aut], Dominik Schulz [aut, cre]

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deseats.pdf |deseats.html✨
deseats/json (API)
NEWS

# Install 'deseats' in R:
install.packages('deseats', repos = c('https://dschulz13.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:
  • CIVLABOR - Monthly Civilian Labor Force Level in the USA
  • CONSUMPTION - Quarterly Real Final Consumption Expenditure for Australia
  • COVID - Daily Confirmed New COVID-19 Cases in Germany
  • DEATHS - Monthly Deaths in Germany
  • ENERGY - Monthly Total Production and Distribution of Electricity, Gas, Steam, and Air Conditioning for Germany
  • EXPENDITURES - Quarterly Personal Consumption Expenditures in the USA
  • GDP - Quarterly US GDP
  • HOUSES - Monthly New One Family Houses Sold in the USA
  • LIVEBIRTHS - Monthly Live Births in Germany
  • NOLABORFORCE - Monthly Number of US Persons Not in the Labor Force
  • RAINFALL - Monthly Average Rainfall in Germany
  • RETAIL - Monthly Total Volume of Retail Trade in Germany
  • SAVINGS - Quarterly Savings of Private Households in Germany
  • SUNSHINE - Monthly Hours of Sunshine in Germany
  • TEMPERATURE - Monthly Average Temperature in Germany

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 2 scripts 293 downloads 42 exports 72 dependencies

Last updated 4 months agofrom:1a54889b99. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 11 2024
R-4.5-win-x86_64OKOct 11 2024
R-4.5-linux-x86_64OKOct 11 2024
R-4.4-win-x86_64OKOct 11 2024
R-4.4-mac-x86_64OKOct 11 2024
R-4.4-mac-aarch64OKOct 11 2024
R-4.3-win-x86_64OKOct 11 2024
R-4.3-mac-x86_64OKOct 11 2024
R-4.3-mac-aarch64OKOct 11 2024

Exports:animatearma_to_ararma_to_maautoplotboundary_methodboundary_method<-BV4.1bwidthbwidth_confintbwidth<-create.gaindeseasonalizedeseatsdetrendexpofittedgainhA_calchamilton_filterkernel_funkernel_fun<-llin_decomplm_decompma_decompmeasuresorder_polyorder_poly<-plotpredictread_tsresidualsrunDecompositions_semiarmaseasonseason<-seasonplotseasonplot_ggselect_bwidthset_optionsshowtrendzoo_to_ts

Dependencies:animationbase64encbslibcachemclicodetoolscolorspacecommonmarkcpp11crayoncurldigestdplyrfansifarverfastmapfontawesomefsfurrrfuturefuture.applygenericsggplot2globalsgluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclelistenvmagickmagrittrMASSMatrixmemoisemgcvmimemunsellnlmeparallellypillarpkgconfigprogressrpromisespurrrR6rappdirsRColorBrewerRcppRcppArmadillorlangsassscalesshinysourcetoolsstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrxtablezoo

Readme and manuals

Help Manual

Help pageTopics
Deseasonalize Time Seriesdeseats-package
Automatic Creation of Animationsanimate
Animate Locally Weighted Regression Resultsanimate,deseats-method
AR Representation of an ARMA Modelarma_to_ar
MA Representation of an ARMA Modelarma_to_ma
Plot Method for Decomposition Results in the Style of ggplot2autoplot,decomp-method
'ggplot2' Plot Method for Class '"deseats_fc"'autoplot,deseats_fc-method
'ggplot2' Plot Method for the Results of a Hamilton Filterautoplot,hfilter-method
Trend and Seasonality Estimation Using the Berlin Procedure 4.1BV4.1
Bootstrapping Confidence Intervals for Locally Weighted Regression Bandwidthsbwidth_confint
Retrieve the Used Bandwidth from an Estimation Objectbwidth,deseats-method bwidth,s_semiarma-method
Monthly Civilian Labor Force Level in the USACIVLABOR
Quarterly Real Final Consumption Expenditure for AustraliaCONSUMPTION
Daily Confirmed New COVID-19 Cases in GermanyCOVID
Create Gain Function from a Linear Time Series Filtercreate.gain
Monthly Deaths in GermanyDEATHS
Locally Weighted Regression for Trend and Seasonality in Equidistant Time Series under Short Memorydeseats
Monthly Total Production and Distribution of Electricity, Gas, Steam, and Air Conditioning for GermanyENERGY
Quarterly Personal Consumption Expenditures in the USAEXPENDITURES
Automatic Creation of Animationsexpo
Exponentiate 'deseats' Forecastsexpo,deseats_fc-method
Fitted Components of the Hamilton Filterfitted,hfilter-method residuals,hfilter-method
Gain Function Genericgain
Obtain gain function values for DeSeaTS Trend and Detrend Filtersgain,deseats-method
Quarterly US GDPGDP
Calculation of Theoretically Optimal Bandwidth and Its ComponentshA_calc
Time Series Filtering Using the Hamilton Filterhamilton_filter
Monthly New One Family Houses Sold in the USAHOUSES
Monthly Live Births in GermanyLIVEBIRTHS
Decomposition of Time Series Using Local Linear Regressionllin_decomp
Decomposition of Time Series Using Linear Regressionlm_decomp
Decomposition of Time Series Using Moving Averagesma_decomp
Forecasting Accuracy Measure Calculationmeasures
Monthly Number of US Persons Not in the Labor ForceNOLABORFORCE
Smoothing Option Genericsboundary_method boundary_method<- bwidth bwidth<- kernel_fun kernel_fun<- order_poly order_poly<- season season<-
Retrieve or Set Smoothing Optionsboundary_method,smoothing_options-method boundary_method<-,smoothing_options-method bwidth,smoothing_options-method bwidth<-,smoothing_options-method kernel_fun,smoothing_options-method kernel_fun<-,smoothing_options-method order_poly,smoothing_options-method order_poly<-,smoothing_options-method season,smoothing_options-method season<-,smoothing_options-method
Plot Method for Decomposition Results in the Style of Base R Plotsplot,decomp-method
Plot Method for Class '"deseats_fc"'plot,deseats_fc-method
Plot Method for the Results of a Hamilton Filterplot,hfilter-method
Point and Interval Forecasts for Seasonal Semi-ARMA Modelspredict,s_semiarma-method
Monthly Average Rainfall in GermanyRAINFALL
Read in a Dataset Directly as an Object of Class '"ts"' or '"mts"'read_ts
Monthly Total Volume of Retail Trade in GermanyRETAIL
Shiny App for Decomposing Seasonal Time SeriesrunDecomposition
Fitting of a Seasonal Semiparametric ARMA Models_semiarma
Quarterly Savings of Private Households in GermanySAVINGS
Creation of Seasonal Plotsseasonplot
Creation of Seasonal Plots in the Style of ggplot2seasonplot_gg
Optimal Bandwidth Estimation for Locally Weighted Regression in Equidistant Time Series under Short Memoryselect_bwidth
Specification of Smoothing Optionsset_options
Printing of 'deseats' Function Resultsshow,deseats-method
Show Method for Objects of Class '"s_semiarma"'show,s_semiarma-method
Show Method for Smoothing Optionsshow,smoothing_options-method
Monthly Hours of Sunshine in GermanySUNSHINE
Monthly Average Temperature in GermanyTEMPERATURE
Obtain Estimated Components of a Time Seriesdeseasonalize detrend trend
Obtain Individual Components of a Decomposed Time Seriesdeseasonalize,decomp-method detrend,decomp-method fitted,decomp-method residuals,decomp-method season,decomp-method trend,decomp-method
Time Series Object Conversion from '"zoo"' to '"ts"'zoo_to_ts