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SLBDD (version 0.0.4)

Statistical Learning for Big Dependent Data

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 Pea and Ruey S. Tsay (2021). ISBN 9781119417385.

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Version

Install

install.packages('SLBDD')

Monthly Downloads

310

Version

0.0.4

License

GPL-3

Maintainer

Antonio El<c3><ad>as

Last Published

April 27th, 2022

Functions in SLBDD (0.0.4)

GCCmatrix

Generalized Cross-Correlation Matrix
FREDMDApril19

Federal Reserve Bank at St Louis.
GCCclus

Clustering of Time Series Using the Generalized Cross Correlation Measure of Linear dependency
Lambda.sel

Select the Penalty Parameter of LASSO-type Linear Regression
DLdata

Create an input data matrix for a Deep learning program that uses time series data.
SelectedSeries

Identified the Series with the Given Order
Stockindexes99world

World Stock Indexes
CPIEurope200015

Price Indexes EUUS
PElectricity1344

Electricity Prices in New England and USA
ClusKur

Cluster Identification Procedure using Projections on Directions of Extreme Kurtosis Coefficient
TaiwanPM25

Hourly PM25 Measurements in Taiwan
UMEdata20002018

Quarterly Economic Series of the European Monetary Union
gap.clus

Gap statistics
chktrans

Check for Possible Non-linear Transformations of a Multiple Time Series
chksea

Check the Seasonality of Each Component of a Multiple Time Series
edqts

Empirical Dynamic Quantile for Visualization of High-Dimensional Time Series
TaiwanAirBox032017

Hourly PM25 Measurements from Air-Box Devices in Taiwan
Summaryccm

Summary Statistics of Cross-Correlation Matrices
quantileBox

Quantile Boxplot
rnnStream

Setup the Input and Output for a Recurrent Neural Network
gdpsimple6c8018

Growth of GDP in 6 Countries
i.plot

Plot a Selected Time Series Using Quantile as the Background
i.qrank

Rank Individual Time Series According to a Given Timewise Quantile Series
i.qplot

Plot the Closest Series to a Given Timewise Quantile Series
sarimaSpec

Automatic Modeling of a Scalar Seasonal Time Series
scatterACF

Scatterplot of Two Selected-lag Autocorrelation Functions
outliers.hdts

Multivariate Outlier Detection
outlierLasso

Outliers LASSO
arimaID

Automatic Modeling of a Scalar Time Series
draw.coef

Random Draw of Coefficients for AR Models and MA Models
mexpimpcnus

Monthly Exports and Imports of China and United States.
arimaSpec

Automatic Modeling of a Scalar Non-Seasonal Time Series
edqplot

Plot the Observed Time Series and Selected EDQs (Empirical Dynamic Quantiles)
mts.plot

Plot Multiple Time Series in One Frame
sSummaryModel

Collects All Models Specified by "sarimaSpec"
sSelectedSeries

Selected Seasonal Time Series
SummaryModel

Collects All Models Specified by "arimaSpec"
mts.qplot

Plot Timewise Quantiles in One Frame
stepp

Stepp
silh.clus

Find the Number of Clusters by the Standard Silhouette Statistics
sim.urarima

Generate Unit-root ARIMA Possibly Seasonal Time Series
outlier.plot

Find Outliers Using an Upper and a Lower Timewise Quantile Series
locations032017

Locations of Air-Box Devices in Taiwan
ts.box

Boxplots of the Medians of Subperiods
tsBoost

Boosting with Simple Linear Regression
dfmpc

Dynamic Factor Model by Principal Components
SummaryOutliers

Summary Outliers
clothing

Cloth sales in China
mdec1to5

Monthly Simple Returns of United States Market Portfolios.
temperatures

World Temperatures