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: 32823
Diverse Datasets for ‘tsibble’.	Github	CRAN	Monthly downloads: 15011
Feature Extraction and Statistics for Time Series.	Github	CRAN	Monthly downloads: 18719
Forecasting Models for Tidy Time Series.	Github	CRAN	Monthly downloads: 20361
Core Tools for Packages in the ‘fable’ Framework.	Github	CRAN	Monthly downloads: 22357
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: 675
Explore Probability Distributions for Bivariate Temporal Granularities: as described in Gupta, Hyndman, Cook & Unwin (2020).	Github

Breaks for Additive Season and Trend: as described in Verbesselt et al (2010a) and Verbesselt et al (2010b).	Github	CRAN	Monthly downloads: 809
Forecasting Functions for Time Series and Linear Models: as described in Hyndman & Khandakar (2008).	Github	CRAN	Monthly downloads: 242483
Generating Time Series with Diverse and Controllable Characteristics: as described in Kang, Hyndman & Li (2020).	Github	CRAN	Monthly downloads: 256
Hierarchical and Grouped Time Series: as described in Hyndman, Ahmed, Athanasopoulos & Shang (2011) and Wickramasuriya, Athanasopoulos & Hyndman (2019).	Github	CRAN	Monthly downloads: 12898
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: 352
STR Decomposition: as described in Dokumentov & Hyndman (2020).		CRAN	Monthly downloads: 1363
Temporal Hierarchical Forecasting: as described in Athanasopoulos et al (2017).	Github	CRAN	Monthly downloads: 11400
Time Series Feature Extraction: as described in Hyndman, Wang & Laptev (2015) and Kang, Hyndman & Smith-Miles (2017).	Github	CRAN	Monthly downloads: 29506

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: 9727
Data sets from Makridakis, Wheelwright & Hyndman (1998), Forecasting: methods and applications, Wiley.	Github	CRAN	Monthly downloads: 11098
Data sets from Hyndman & Athanasopoulos (2014) Forecasting: principles and practice, OTexts.		CRAN	Monthly downloads: 7823
Data sets from Hyndman & Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts.	Github	CRAN	Monthly downloads: 13192
Data sets from Hyndman & Athanasopoulos (2021) Forecasting: principles and practice, 3rd edition, OTexts.	Github	CRAN	Monthly downloads: 17640
Data from the M-Competitions.	Github
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: 237
Anomaly Detection in High Dimensional and Temporal Data: as described in Talagala, Hyndman & Smith-Miles (2021).	Github	CRAN	Monthly downloads: 739
Outlier Detection in Data Streams: as described in Talagala, Hyndman, Smith-Miles, Kandanaarachichi & Muñoz (2020).	Github	CRAN	Monthly downloads: 155
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: 184

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: 3511
Functional Data Sets.		CRAN	Monthly downloads: 44314
Functional Time Series Analysis.		CRAN	Monthly downloads: 6185
Bagplots, Boxplots and Rainbow Plots for Functional Data: as described in Hyndman & Shang (2010).		CRAN	Monthly downloads: 39557
Seasonal Functional Autoregressive Models: as described in Zamani, Haghbin, Hashemi & Hyndman (2001).	Github	CRAN	Monthly downloads: 204
Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects: as described in Dokumentov, Hyndman & Tickle (2018).		CRAN	Monthly downloads: 494

‘binb’ is not ‘Beamer’.	Github	CRAN	Monthly downloads: 402
Consolidated tools and templates for staff at Monash University.	Github
Article Formats for R Markdown.	Github	CRAN	Monthly downloads: 6726
Curriculum Vitae for R Markdown.	Github	CRAN	Monthly downloads: 1695

International Cricket Data.	Github	CRAN	Monthly downloads: 381
Exploring Election and Census Highly Informative Data Nationally for Australia: as described in Forbes, Cook & Hyndman (2020).	Github	CRAN	Monthly downloads: 268
Visualisation of Highest Density Regions in ‘ggplot2’: as described in Hyndman (1996).	Github	CRAN	Monthly downloads: 218
Highest Density Regions and Conditional Density Estimation: as described in Hyndman (1996) and Hyndman, Bashtannyk & Grunwald (1996).	Github	CRAN	Monthly downloads: 11830
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.