CRAN task views
Selected R packages I’ve coauthored
Tidy time series analysis and forecasting
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Tidy Temporal Data Frames and Tools: as described in Wang, Cook & Hyndman (2020). | Github | CRAN |
Monthly downloads: 17479 |
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Diverse Datasets for ‘tsibble’. | Github | CRAN |
Monthly downloads: 5296 |
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Feature Extraction and Statistics for Time Series. | Github | CRAN |
Monthly downloads: 9129 |
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Forecasting Models for Tidy Time Series. | Github | CRAN |
Monthly downloads: 8504 |
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Core Tools for Packages in the ‘fable’ Framework. | Github | CRAN |
Monthly downloads: 10171 |
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Fast Additive Switching of Seasonality, Trend and Exogenous Regressors. | Github | ||
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Supporting Graphs for Analysing Time Series: as described in Wang, Cook & Hyndman (2020). | Github | CRAN |
Monthly downloads: 839 |
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Explore Probability Distributions for Bivariate Temporal Granularities: as described in Gupta, Hyndman, Cook & Unwin (2020). | Github | CRAN |
Monthly downloads: 548 |
Other time series analysis and forecasting
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Breaks for Additive Season and Trend: as described in Verbesselt et al (2010a) and Verbesselt et al (2010b). | Github | CRAN |
Monthly downloads: 1858 |
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Forecasting Functions for Time Series and Linear Models: as described in Hyndman & Khandakar (2008). | Github | CRAN |
Monthly downloads: 255899 |
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Generating Time Series with Diverse and Controllable Characteristics: as described in Kang, Hyndman & Li (2020). | Github | CRAN |
Monthly downloads: 551 |
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Hierarchical and Grouped Time Series: as described in Hyndman, Ahmed, Athanasopoulos & Shang (2011) and Wickramasuriya, Athanasopoulos & Hyndman (2019). | Github | CRAN |
Monthly downloads: 23563 |
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Monash Electricity Forecasting Model: as described in Hyndman & Fan (2010). | Github | ||
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Feature-Based Forecast Model Selection: as described in Talagala, Hyndman & Athanasopoulos (2018). | Github | CRAN |
Monthly downloads: 680 |
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STR Decomposition: as described in Dokumentov & Hyndman (2020). | CRAN |
Monthly downloads: 785 |
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Temporal Hierarchical Forecasting: as described in Athanasopoulos et al (2017). | Github | CRAN |
Monthly downloads: 14593 |
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Time Series Feature Extraction: as described in Hyndman, Wang & Laptev (2015) and Kang, Hyndman & Smith-Miles (2017). | Github | CRAN |
Monthly downloads: 9300 |
Time series data
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Time series data from comp-engine.org. | Github | ||
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Data sets from Hyndman, Koehler, Ord & Snyder (2008), Forecasting with exponential smoothing: the state space approach, Springer. | Github | CRAN |
Monthly downloads: 17048 |
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Data sets from Makridakis, Wheelwright & Hyndman (1998), Forecasting: methods and applications, Wiley. | Github | CRAN |
Monthly downloads: 17157 |
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Data sets from Hyndman & Athanasopoulos (2014) Forecasting: principles and practice, OTexts. | CRAN |
Monthly downloads: 3832 |
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Data sets from Hyndman & Athanasopoulos (2018) Forecasting: principles and practice, 2nd edition, OTexts. | Github | CRAN |
Monthly downloads: 17906 |
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Data sets from Hyndman & Athanasopoulos (2021) Forecasting: principles and practice, 3rd edition, OTexts. | Github | CRAN |
Monthly downloads: 5716 |
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Data from the M-Competitions. | Github | CRAN |
Monthly downloads: 7019 |
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Import and explore freely available Australian data sets. | Github | ||
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Time series data from various forecasting competitions. | Github | ||
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Time Series Data Library. | Github |
Anomaly detection
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Leave One Out Kernel Density Estimates for Outlier Detection: as described in Kandanaarachchi and Hyndman (2021). | Github | CRAN |
Monthly downloads: 403 |
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Anomaly Detection in High Dimensional and Temporal Data: as described in Talagala, Hyndman & Smith-Miles (2021). | Github | CRAN |
Monthly downloads: 402 |
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Outlier Detection in Data Streams: as described in Talagala, Hyndman, Smith-Miles, Kandanaarachichi & Muñoz (2020). | Github | CRAN |
Monthly downloads: 416 |
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Outlier Detection in Data from Water-Quality Sensors: as described in Talagala, Hyndman, Leigh, Mengersen & Smith-Miles (2019). | Github |
Functional data and demography
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Australian Demographic Data Bank. | Github | ||
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Forecasting Mortality, Fertility, Migration and Population Data: as described in Hyndman, Booth & Yasmeen (2013) and Hyndman & Ullah (2007). | Github | CRAN |
Monthly downloads: 1847 |
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Functional Data Sets. | CRAN |
Monthly downloads: 13341 |
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Functional Time Series Analysis. | CRAN |
Monthly downloads: 2340 |
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Bagplots, Boxplots and Rainbow Plots for Functional Data: as described in Hyndman & Shang (2010). | CRAN |
Monthly downloads: 13469 |
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Seasonal Functional Autoregressive Models: as described in Zamani, Haghbin, Hashemi & Hyndman (2001). | Github | CRAN |
Monthly downloads: 495 |
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Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects: as described in Dokumentov, Hyndman & Tickle (2018). | CRAN |
Monthly downloads: 450 |
Rmarkdown
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‘binb’ is not ‘Beamer’. | Github | CRAN |
Monthly downloads: 687 |
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Consolidated tools and templates for staff at Monash University. | Github | ||
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Curriculum Vitae for R Markdown. | Github | CRAN |
Monthly downloads: 2249 |
Other
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International Cricket Data. | Github | ||
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Exploring Election and Census Highly Informative Data Nationally for Australia: as described in Forbes, Cook & Hyndman (2020). | Github | CRAN |
Monthly downloads: 631 |
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Evolutionary model-based multiresponse approach. | CRAN |
Monthly downloads: 515 |
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Highest Density Regions and Conditional Density Estimation: as described in Hyndman (1996) and Hyndman, Bashtannyk & Grunwald (1996). | Github | CRAN |
Monthly downloads: 13193 |
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Australian Popular Baby Names. | Github | ||
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Find details about my R packages. | Github | ||
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Tools to assist with academic promotions. | Github |