tsutils: tsutils: Time Series Exploration, Modelling and Forecasting

In tsutils: Time Series Exploration, Modelling and Forecasting

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

• abc: ABC analysis.

• xyz: XYZ analysis.

• abcxyz: ABC-XYZ analyses visualisation.

Quality of life

• geomean: geometric mean.

• lambdaseq: generate sequence of lambda for LASSO regression.

• leadtrail: remove leading/training zeros/NAs.

• wins: winsorisation, including vectorised versions colWins and rowWins.

Time series data

• referrals: A&E monthly referrals.

tsutils documentation built on Nov. 15, 2023, 1:08 a.m.