| 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
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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
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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
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Sthief: temporal hierarchy S matrix. -
plotSthief: plot temporal hierarchy S matrix.
Forecasting process modelling
Quality of life
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geomean: geometric mean. -
lambdaseq: generate sequence of lambda for LASSO regression. -
leadtrail: remove leading/training zeros/NAs. -
wins: winsorisation, including vectorised versionscolWinsandrowWins.
Time series data
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referrals: A&E monthly referrals.