Package: dsa 1.0.12

Daniel Ollech

dsa: Seasonal Adjustment of Daily Time Series

Seasonal- and calendar adjustment of time series with daily frequency using the DSA approach developed by Ollech, Daniel (2018): Seasonal adjustment of daily time series. Bundesbank Discussion Paper 41/2018.

Authors:Daniel Ollech [aut, cre]

dsa_1.0.12.tar.gz
dsa_1.0.12.tar.gz(r-4.5-noble)dsa_1.0.12.tar.gz(r-4.4-noble)
dsa_1.0.12.tgz(r-4.4-emscripten)dsa_1.0.12.tgz(r-4.3-emscripten)
dsa.pdf |dsa.html✨
dsa/json (API)
NEWS

# Install 'dsa' in R:

install.packages('dsa', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openjdk– OpenJDK Java runtime, using Hotspot JIT

Datasets:

daily_data - Exemplary time series
dsa_examples - Exemplary dsa outputs
holidays - Data set for frequently used regressors

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

3.22 score 1 stars 1 packages 55 scripts 352 downloads 20 exports 76 dependencies

Last updated 3 years agofrom:291044d46c. Checks:OK: 1 NOTE: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Oct 05 2024
R-4.5-linux	NOTE	Oct 05 2024

Exports:daily_sim del_names Descaler dsa freq_xts get_original get_sa get_trend make_cal make_dummy make_holiday multi_xts2ts output plot_spectrum Scaler to_weekly ts_sum ts2xts xts2ts xtsplot

Dependencies:base64enc bslib cachem cli colorspace curl digest dygraphs evaluate fansi farver fastmap fontawesome forecast fracdiff fs generics ggplot2 glue gridExtra gtable highr htmltools htmlwidgets isoband jquerylib jsonlite knitr labeling lattice lifecycle lmtest magrittr MASS Matrix memoise mgcv mime munsell nlme nnet pillar pkgconfig plyr quadprog quantmod R2HTML R6 rappdirs RColorBrewer Rcpp RcppArmadillo reshape2 rJava rlang rmarkdown sass scales seastests stringi stringr tibble timeDate tinytex tseries tsoutliers TTR urca utf8 vctrs viridisLite withr xfun xts yaml zoo

dsa-vignette

Rendered fromdsa-vignette.Rmdusingknitr::rmarkdownon Oct 05 2024.

Last update: 2021-06-21
Started: 2019-01-28

Citation

Readme and manuals

Help Manual

Help page	Topics
Exemplary time series	daily_data
Create a simple, exemplary, seasonal, daily time series	daily_sim
Delete name of xts	del_names
Invert taking logs and differences of a time series	Descaler
Seasonally Adjust Daily Time Series	dsa
Exemplary dsa outputs	dsa_examples
Obtain the frequency of an xts time series	freq_xts
Get Original Time Series	get_original
Get Seasonally Adjusted Series	get_sa
Get Trend-Cycle	get_trend
Data set for frequently used regressors	holidays
Creating holiday regressor that increases linearly up to holiday and decreases afterwards	make_cal
Creating set of dummy variables for specified Holidays	make_dummy
Creating Holiday dummy	make_holiday
Change multiple xts to a multivariate ts	multi_xts2ts
Creating Output for dsa	output
Plot the periodogram of a daily time series	plot_spectrum
Plot daily time series	plot.daily
Print daily time series	print.daily
Take logs and differences of a time series	Scaler
Change a daily to a weekly differenced time series	to_weekly
Add time series	ts_sum
Change ts to xts	ts2xts
Change xts to ts	xts2ts
Create a plot for xts series	xtsplot