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deseats  

Data-Driven Locally Weighted Regression for Trend and Seasonality in TS
View on CRAN: Click here


Download and install deseats package within the R console
Install from CRAN:
install.packages("deseats")

Install from Github:
library("remotes")
install_github("cran/deseats")

Install by package version:
library("remotes")
install_version("deseats", "1.1.0")



Attach the package and use:
library("deseats")
Maintained by
Dominik Schulz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-11-08
Latest Update: 2023-11-08
Description:
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) and Feng, Y., Gries, T., and Fritz, M. (2020) 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) . Permission to include this procedure was kindly provided by the Federal Statistical Office of Germany.
How to cite:
Dominik Schulz (2023). deseats: Data-Driven Locally Weighted Regression for Trend and Seasonality in TS. R package version 1.1.0, https://cran.r-project.org/web/packages/deseats. Accessed 12 Mar. 2025.
Previous versions and publish date:
1.0.0 (2023-11-08 20:50)
Other packages that cited deseats R package
View deseats citation profile
Other R packages that deseats depends, imports, suggests or enhances
Complete documentation for deseats
Functions, R codes and Examples using the deseats R package
Some associated functions: BV4.1 . CIVLABOR . CONSUMPTION . COVID . DEATHS . ENERGY . EXPENDITURES . GDP . HOUSES . LIVEBIRTHS . NOLABORFORCE . RAINFALL . RETAIL . SAVINGS . SUNSHINE . TEMPERATURE . animate-deseats-method . animate . arma_to_ar . arma_to_ma . autoplot-decomp-method . autoplot-deseats_fc-method . autoplot-hfilter-method . bwidth-deseats-method . bwidth_confint . create.gain . deseats-package . deseats . expo-deseats_fc-method . expo . fitted-hfilter-method . gain-deseats-method . gain . hA_calc . hamilton_filter . llin_decomp . lm_decomp . ma_decomp . measures . order_poly-smoothing_options-method . order_poly . plot-decomp-method . plot-deseats_fc-method . plot-hfilter-method . predict-s_semiarma-method . read_ts . runDecomposition . s_semiarma . select_bwidth . set_options . show-deseats-method . show-s_semiarma-method . show-smoothing_options-method . trend-decomp-method . trend . zoo_to_ts . 
Some associated R codes: AttachMessage.R . RcppExports.R . accuracy_measures.R . arima_no_warn.R . bwidth_bootstrap.R . class-bv41.R . class-decomp.R . class-deseats.R . class-deseats_fc.R . class-hfilter.R . class-llindecomp.R . class-lmdecomp.R . class-madecomp.R . class-s_semiarma.R . class-smoothing_options.R . data_documentation.R . deseats-package.R . fitting_functions.R . forecasting_functions.R . gain_function.R . generics.R . hA_calc.R . helper_functions.R . linear_filters.R . runDecomposition.R . subplot_functions.R . ts_conversion.R .  Full deseats package functions and examples
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