tsutils {tsutils} | R Documentation |
tsutils: Time Series Exploration, Modelling and Forecasting
Description
The tsutils package provides functions to support various aspects of time series and forecasting modelling. In particular this package includes: (i) tests and visualisations that can help the modeller explore time series components and perform decomposition; (ii) modelling shortcuts, such as functions to construct lagmatrices and seasonal dummy variables of various forms; (iii) an implementation of the Theta method; (iv) tools to facilitate the design of the forecasting process, such as ABC-XYZ analyses; and (v) "quality of life" tools, such as treating time series for trailing and leading values.
Time series exploration
-
cmav
: centred moving average. -
coxstuart
: Cox-Stuart test for location/dispersion. -
decomp
: classical time series decomposition. -
seasplot
: construct seasonal plots. -
trendtest
: test a time series for trend.
Time series modelling
-
getOptK
: optimal temporal aggregation level for AR(1), MA(1), ARMA(1,1). -
lagmatrix
: create leads/lags of variable. -
nemenyi
: nonparametric multiple comparisons. -
residout
: construct control chart of residuals. -
seasdummy
: create seasonal dummies. -
theta
: Theta method.
Hierarchical time series
-
Sthief
: temporal hierarchy S matrix. -
plotSthief
: plot temporal hierarchy S matrix.
Forecasting process modelling
Quality of life
-
geomean
: geometric mean. -
lambdaseq
: generate sequence of lambda for LASSO regression. -
leadtrail
: remove leading/training zeros/NAs. -
wins
: winsorisation, including vectorised versionscolWins
androwWins
.
Time series data
-
referrals
: A&E monthly referrals.