Statistical Learning for Big Dependent Data

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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


0.0.2 by Antonio Elias, a month ago

Browse source code at

Authors: Angela Caro [aut] , Antonio Elias [aut, cre] , Daniel Peña [aut] , Ruey S. Tsay [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports stats, glmnet, corpcor, forecast, gsarima, cluster, fGarch, imputeTS, methods, MASS, MTS, TSclust, tsoutliers, Matrix, matrixcalc, rnn

See at CRAN