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tsaux (version 1.0.0)

Time Series Forecasting Auxiliary Functions

Description

A suite of auxiliary functions that enhance time series estimation and forecasting, including a robust anomaly detection routine based on Chen and Liu (1993) (imported and wrapped from the 'tsoutliers' package), utilities for managing calendar and time conversions, performance metrics to assess both point forecasts and distributional predictions, advanced simulation by allowing the generation of time series components—such as trend, seasonal, ARMA, irregular, and anomalies—in a modular fashion based on the innovations form of the state space model and a number of transformation methods including Box-Cox, Logit, 'Softplus-Logit' and Sigmoid.

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Install

install.packages('tsaux')

Monthly Downloads

308

Version

1.0.0

License

GPL-2

Issues

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Maintainer

Alexios Ghalanos

Last Published

March 31st, 2025

Functions in tsaux (1.0.0)

box_cox

Box-Cox transform specification
fourier_series

Fourier terms for modeling seasonality
check_xreg

Checks on regressor matrix.
lines.issm.component

Add Connected Line Segments to a Simulation Object
future_dates

Generate Regular Interval Future Dates
calendar_eom

End of Month Date
sigmoid

The sigmoid transformation
seasonality_test

Simple Seasonality Test
mixture_modelspec

Ensemble Setup
plot.issm.component

Plot Simulation Object
seasonal_dummies

Seasonal Dummies
sampling_sequence

Sampling frequency sequence
calendar_eoq

End of Quarter Date
calendar_eow

End of Week Date
process_time

POSIXct Processing
sampling_frequency

Infers the sampling frequency of a time series
tsdecompose.issm.component

State Decomposition
tsaux-package

tsaux: Time Series Forecasting Auxiliary Functions
tstransform

General transformation function
logit

The logit transformation
tsensemble.tssim.mixture

Ensembling of Simulations
tslinear

Linear Time Series Filter
softlogit

The softplus logit transformation
time_splits

Generate Train/Test Splits
mape

Forecast Performance Metrics
add_anomaly

Anomaly Component
auto_clean

Automatic Cleaning of Outliers and Temporary Changes
add_arma

ARMA Component
add_regressor

Regressor Component
auto_regressors

Automatic Detection of Outliers, Trends Breaks and Temporary Changes
add_transform

Transform
add_polynomial

Polynomial Trend Component
add_custom

Custom Component
add_seasonal

Seasonal Trend Component
initialize_simulator

Simulator Initializer
additive_outlier

Anomaly Creation
calendar_eoy

End of Year Date