Software I've written

This page provides links to R packages I have (co)authored. The most recent versions of most packages are on github. Most packages are also on CRAN.

Nine data sets, taken from the Australian Demographic Data Bank version 3.2b, courtesy of Len Smith.
Automatic identification of breaks for additive season and trend, designed for use with remote sensing data. [CRAN]
International Cricket Data.
Provides a large number of functions for handling demographic statistics, modelling and forecasting. In particular, it implements lifetable calculations; Lee-Carter modelling and variants; functional data analysis of mortality rates, fertility rates, net migration numbers; and stochastic population forecasting. [CRAN]
Exploring Election and Census Highly Informative Data Nationally for Australia. Data from the 2013 and 2016 Australian Federal Elections and the 2011 and 2016 Australian Censuses for each House of Representatives electorate, along with some tools for visualizing and analysing the data. [CRAN]
The evolutionary model-based multiresponse approach (EMMA) is a novel methodology to process optimisation and product improvement. The approach is suitable to contexts in which the experimental cost and/or time limit the number of implementable trials. [CRAN]
Data sets from Hyndman, Koehler, Ord and Snyder (2008) Forecasting with exponential smoothing: the state space approach, Springer: Berlin. [CRAN]
Functional data sets useful for testing new methods. [CRAN]
Data sets from Makridakis, Wheelwright and Hyndman (1998) Forecasting: methods and applications, Wiley & Sons: New York. [CRAN]
Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling. [CRAN]
Data sets from Hyndman & Athanasopoulos (2014) Forecasting: principles and practice, OTexts: Melbourne. [CRAN]
Data sets from Hyndman & Athanasopoulos (2017) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne. [CRAN]
Methods and tools for modelling and forecasting functional time series. [CRAN]
Tools for the computation of highest density regions in one and two dimensions, kernel estimation of univariate density functions conditional on one covariate, and multimodal regression. [CRAN]
Methods for visualizing, analysing and forecasting hierarchical time series. [CRAN]
The 1001 time series from the M-competition (Makridakis et al. 1982) and the 3003 time series from the IJF-M3 competition (Makridakis and Hibon, 2000). [CRAN]
A set of tools for implementing the Monash Electricity Forecasting Model based on the paper by Hyndman and Fan (2010).
Tools to import and explore Australian data sets. Data imported from and
Plots for functional data: rainbow plot, functional bagplot, functional HDR boxplot. [CRAN]
Dynamic documents for R. [CRAN]
Forecasting time series with robust exponential smoothing. [CRAN]
Smoothing demographic data with period and cohort effects. The method uses bivariate thin plate splines, bivariate lasso-type regularization, and allows for both period and cohort effects. Thus the mortality rates are modelled as the sum of four components: a smooth bivariate function of age and time, smooth one-dimensional cohort effects, smooth one-dimensional period effects and random errors. The methods are described in Dokumentov, A., and Hyndman, R.J. (2014) Bivariate data with ridges: two-dimensional smoothing of mortality rates. [CRAN]
STR time series decomposition. The methods are described in Dokumentov, A., and Hyndman, R.J. (2016) STR: A Seasonal-Trend Decomposition Procedure Based on Regression. [CRAN]
Supporting Graphs for Analysing Time Series. Tools for plotting temporal data using the tidyverse and grammar of graphics framework. [CRAN]
Temporal Hierarchical Forecasting. The methods are described in Forecasting with temporal hierarchies, co-authored with George Athanasopoulos, Nikolaos Kourentzes and Fotios Petropoulos. [CRAN]
Time Series Competition Data
Time Series Feature Extraction.
Tidy Temporal Data Frames and Tools [CRAN]