CRAN task views

Selected R packages I’ve coauthored

Tidy Temporal Data Frames and Tools: as described in Wang, Cook & Hyndman (2020).	Github	CRAN	Monthly downloads: 29106
Diverse Datasets for ‘tsibble’.	Github	CRAN	Monthly downloads: 9218
Feature Extraction and Statistics for Time Series.	Github	CRAN	Monthly downloads: 15814
Forecasting Models for Tidy Time Series.	Github	CRAN	Monthly downloads: 17186
Core Tools for Packages in the ‘fable’ Framework.	Github	CRAN	Monthly downloads: 18563
Fast Additive Switching of Seasonality, Trend and Exogenous Regressors.	Github
Supporting Graphs for Analysing Time Series: as described in Wang, Cook & Hyndman (2020).	Github	CRAN	Monthly downloads: 541
Explore Probability Distributions for Bivariate Temporal Granularities: as described in Gupta, Hyndman, Cook & Unwin (2020).	Github	CRAN	Monthly downloads: 211

Breaks for Additive Season and Trend: as described in Verbesselt et al (2010a) and Verbesselt et al (2010b).	Github	CRAN	Monthly downloads: 1069
CONDitional UI for Time Series normalisation.	Github
Forecasting Functions for Time Series and Linear Models: as described in Hyndman & Khandakar (2008).	Github	CRAN	Monthly downloads: 223556
Generating Time Series with Diverse and Controllable Characteristics: as described in Kang, Hyndman & Li (2020).	Github	CRAN	Monthly downloads: 351
Hierarchical and Grouped Time Series: as described in Hyndman, Ahmed, Athanasopoulos & Shang (2011) and Wickramasuriya, Athanasopoulos & Hyndman (2019).	Github	CRAN	Monthly downloads: 9335
Monash Electricity Forecasting Model: as described in Hyndman & Fan (2010).	Github
Feature-Based Forecast Model Selection: as described in Talagala, Hyndman & Athanasopoulos (2018).	Github	CRAN	Monthly downloads: 275
STR Decomposition: as described in Dokumentov & Hyndman (2020).		CRAN	Monthly downloads: 588
Temporal Hierarchical Forecasting: as described in Athanasopoulos et al (2017).	Github	CRAN	Monthly downloads: 10982
Time Series Feature Extraction: as described in Hyndman, Wang & Laptev (2015) and Kang, Hyndman & Smith-Miles (2017).	Github	CRAN	Monthly downloads: 27929

Time series data from comp-engine.org.	Github
Data sets from Hyndman, Koehler, Ord & Snyder (2008), Forecasting with exponential smoothing: the state space approach, Springer.	Github	CRAN	Monthly downloads: 7144
Data sets from Makridakis, Wheelwright & Hyndman (1998), Forecasting: methods and applications, Wiley.	Github	CRAN	Monthly downloads: 7956
Data sets from Hyndman & Athanasopoulos (2014) Forecasting: principles and practice, OTexts.		CRAN	Monthly downloads: 2082
Data sets from Hyndman & Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts.	Github	CRAN	Monthly downloads: 9192
Data sets from Hyndman & Athanasopoulos (2021) Forecasting: principles and practice, 3rd edition, OTexts.	Github	CRAN	Monthly downloads: 11893
Data from the M-Competitions.	Github	CRAN	Monthly downloads: 4213
Import and explore freely available Australian data sets.	Github
Time series data from various forecasting competitions.	Github
Time Series Data Library.	Github

Leave One Out Kernel Density Estimates for Outlier Detection: as described in Kandanaarachchi and Hyndman (2021).	Github	CRAN	Monthly downloads: 242
Anomaly Detection in High Dimensional and Temporal Data: as described in Talagala, Hyndman & Smith-Miles (2021).	Github	CRAN	Monthly downloads: 208
Outlier Detection in Data Streams: as described in Talagala, Hyndman, Smith-Miles, Kandanaarachichi & Muñoz (2020).	Github	CRAN	Monthly downloads: 121
Outlier Detection in Data from Water-Quality Sensors: as described in Talagala, Hyndman, Leigh, Mengersen & Smith-Miles (2019).	Github
Anomaly Detection in Temporal Networks: as described in Kandanaarachchi & Hyndman (2022).	Github	CRAN	Monthly downloads: 143

Australian Demographic Data Bank.	Github
Forecasting Mortality, Fertility, Migration and Population Data: as described in Hyndman, Booth & Yasmeen (2013) and Hyndman & Ullah (2007).	Github	CRAN	Monthly downloads: 2220
Functional Data Sets.		CRAN	Monthly downloads: 10337
Functional Time Series Analysis.		CRAN	Monthly downloads: 2827
Bagplots, Boxplots and Rainbow Plots for Functional Data: as described in Hyndman & Shang (2010).		CRAN	Monthly downloads: 10603
Seasonal Functional Autoregressive Models: as described in Zamani, Haghbin, Hashemi & Hyndman (2001).	Github	CRAN	Monthly downloads: 209
Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects: as described in Dokumentov, Hyndman & Tickle (2018).		CRAN	Monthly downloads: 141
Tidy Analysis Tools for Mortality, Fertility, Migration and Population Data.	Github

‘binb’ is not ‘Beamer’.	Github	CRAN	Monthly downloads: 397
Consolidated tools and templates for staff at Monash University.	Github
Article Formats for R Markdown.	Github	CRAN	Monthly downloads: 7078
Curriculum Vitae for R Markdown.	Github	CRAN	Monthly downloads: 1587

Forecasting Functions for the Transport Accident Commission.	Github
International Cricket Data.	Github	CRAN	Monthly downloads: 404
Exploring Election and Census Highly Informative Data Nationally for Australia: as described in Forbes, Cook & Hyndman (2020).	Github	CRAN	Monthly downloads: 251
Visualisation of Highest Density Regions in ‘ggplot2’: as described in Hyndman (1996).	Github	CRAN	Monthly downloads: 178
Highest Density Regions and Conditional Density Estimation: as described in Hyndman (1996) and Hyndman, Bashtannyk & Grunwald (1996).	Github	CRAN	Monthly downloads: 10506
Australian Popular Baby Names.	Github
Find details about R packages on CRAN or github.	Github
Tools to assist with academic promotions.	Github

Create a letter on Monash University letterhead.

quarto use template numbats/monash-quarto-letter

Create a memo with optional Monash University branding.

quarto use template numbats/monash-quarto-memo

Create a working paper for the Department of Econometrics & Business Statistics, Monash University.

quarto use template numbats/monash-quarto-workingpaper

Create a Monash University report.

quarto use template numbats/monash-quarto-report

Create a Monash University thesis.

Either fork or download the repository to get started.