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SLBDD  

Statistical Learning for Big Dependent Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("SLBDD", "0.0.4")



Attach the package and use:
library("SLBDD")
Maintained by
Antonio Elias
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-02-16
Latest Update: 2022-04-27
Description:
Programs for analyzing large-scale time series data. They include functions for automatic specification and estimation of univariate time series, for clustering time series, for multivariate outlier detections, for quantile plotting of many time series, for dynamic factor models and for creating input data for deep learning programs. Examples of using the package can be found in the Wiley book 'Statistical Learning with Big Dependent Data' by Daniel Peña and Ruey S. Tsay (2021). ISBN 9781119417385.
How to cite:
Antonio Elias (2021). SLBDD: Statistical Learning for Big Dependent Data. R package version 0.0.4, https://cran.r-project.org/web/packages/SLBDD. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.0.1 (2021-02-16 11:10), 0.0.2 (2021-03-27 09:00), 0.0.3 (2022-03-16 10:10), 0.0.4 (2022-04-27 13:20)
Other packages that cited SLBDD R package
View SLBDD citation profile
Other R packages that SLBDD depends, imports, suggests or enhances
Complete documentation for SLBDD
Functions, R codes and Examples using the SLBDD R package
Some associated functions: CPIEurope200015 . ClusKur . DLdata . FREDMDApril19 . GCCclus . GCCmatrix . Lambda.sel . PElectricity1344 . SelectedSeries . Stockindexes99world . SummaryModel . SummaryOutliers . Summaryccm . TaiwanAirBox032017 . TaiwanPM25 . UMEdata20002018 . arimaID . arimaSpec . chksea . chktrans . clothing . dfmpc . draw.coef . edqplot . edqts . gap.clus . gdpsimple6c8018 . i.plot . i.qplot . i.qrank . locations032017 . mdec1to5 . mexpimpcnus . mts.plot . mts.qplot . outlier.plot . outlierLasso . outliers.hdts . quantileBox . rnnStream . sSelectedSeries . sSummaryModel . sarimaSpec . scatterACF . silh.clus . sim.urarima . stepp . temperatures . ts.box . tsBoost . 
Some associated R codes: CPIEurope200015-data.R . DFMPC.R . DLdata.R . EDQplot.R . EDQts.R . FREDMDApril19.R . GCCclus.R . GCCmatrix.R . Lambda.sel.R . Pelectricity1344-data.R . Stockindexes99world-data.R . TaiwanAirBox032017-data.R . TaiwanPM25-data.R . UMEdata20002018-data.R . arimaID.R . arimaSpec.R . chksea.R . chktrans.R . clothing-data.R . cluskur.R . drawcoef.R . gap.clus.R . gdpsimple6c8018-data.R . i.plot.R . i.qplot.R . i.qrank.R . locations032017-data.R . mdec1to5-data.R . mexpimpcnus-data.R . mts.plot.R . mts.qplot.R . outlier.plot.R . outlierLasso.R . outliers.hdts.R . quantilebox.R . rnnStream.R . sSelectedSeries.R . sarimaSpec.R . scatterACF.R . selectedseries.R . silh.clus.R . sim.urarima.R . ssummarymodel.R . stepp.R . summaryccm.R . summarymodel.R . summaryoutliers.R . temperatures-data.R . tsBoost.R . tsBox.R .  Full SLBDD package functions and examples
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