⚠️ When I was actively maintaining these software tools, all scripts and examples were fully reproducible. Currently, I’m no longer involved in their regular updates and cannot guarantee compatibility with the latest compilers or software platforms.
tsdecomp Decomposition of Time Series Data  

ARIMA-model-based decomposition of quarterly and monthly time series data. The methodology is developed and described, among others, in Burman (1980, doi:10.2307/2982132) and Hillmer and Tiao (1982, doi:10.2307/2287770).

CRAN | Document

tsoutliers Detection of Outliers in Time Series  

This package implements a procedure based on the approach described in Chen and Liu (1993, doi:10.2307/2290724) for automatic detection of outliers in time series. Innovational outliers, additive outliers, level shifts, temporary changes and seasonal level shifts are considered.

CRAN | Document | Previous devel source

bsm.airp Fit the Basic Structural Model to the Airline Passengers Data

This package provides functions and scripts to replicate the results discussed in the document 101 variations on a maximum likelihood procedure to fit the basic structural time series model.

Source | Reference guide | Document

stsm.em Expectation-Maximization Algorithm for Structural Time Series Models

The package implements the standard EM algorithm described in the litetature for pure variance structural time series models. A modified version described in the document linked below is also implemented. The computations of the latter algorithm are suited to be computed in parallel. A parallel implementation using Cilk plus is available in the package.

Source | Document

temper Functions for the Analysis of Temperature Trends in Alaska

This package contains the functions used to obtain the results discussed in the paper "Trends in Alaska Temperature Data. Towards a More Realistic Approach", Climate Dynamics.

Source | DOI

stsm Structural Time Series Models

This package provides some functions to fit time series models by means of the traditional maximization of the time domain likelihood function via quasi-Newton algorithm. It is used as a reference to compare the results based on the scoring algorithm to maximize the frequency domain likelihood function.

CRAN | Document | code chunks

stsm.class Class and Methods for Structural Time Series Models

This package defines a class and several methods to work with structural time series models.

CRAN

KFKSDS Kalman Filter, Kalman Smoother and Disturbance Smoother

This package provides a naive implementation of the Kalman filter, Kalman smoother and disturbance smoother.

CRAN

meboot Maximum Entropy Bootstrap for Time Series

The package implements the maximum entropy bootstrap proposed by Prof. H.D. Vinod.

CRAN | JSS paper

partsm Periodic Autoregressive Time Series Models

This package was developed as a pedagogical exercise while reading the book Periodicity and Stochastic Trends in Economic Time Series Franses, P.H.B.F. (1996) (info). The package replicates some of the results shown in the first eight chapters of the book.
Acknowledgements: Many thanks to Matthieu Stigler for maintaining the package active on CRAN.

CRAN | Document

uroot Unit Root Tests for Seasonal Time Series

Seasonal unit roots and seasonal stability tests. P-values based on response surface regressions are available for both tests. P-values based on bootstrap are available for seasonal unit root tests. A parallel implementation of the bootstrap method requires a CUDA capable GPU with compute capability >= 3.0, otherwise a debugging version fully coded in R is used.

CRAN | Document 1 | Document 2