Bibliography

Bache, Stefan Milton, and Hadley Wickham. 2014. Magrittr: A Forward-Pipe Operator for R. https://CRAN.R-project.org/package=magrittr.

Becker, Richard A., William S. Cleveland, and Ming-Jen Shyu. 1996. “The Visual Design and Control of Trellis Display.” Journal of Computational and Graphical Statistics 5 (2): 123–55. https://doi.org/10.1080/10618600.1996.10474701.

Bengtsson, Henrik. 2019. Future: Unified Parallel and Distributed Processing in R for Everyone. https://CRAN.R-project.org/package=future.

Box, George Edward Pelham, and Gwilym Jenkins. 1990. Time Series Analysis, Forecasting and Control. San Francisco, CA, USA: Holden-Day, Inc.

Buja, Andreas, Daniel Asimov, Catherine Hurley, and John A. McDonald. 1988. “Elements of a Viewing Pipeline for Data Analysis.” In Dynamic Graphics for Statistics, edited by William S. Cleveland and Marylyn E. McGill. Belmont, California: Wadsworth, Inc.

Bureau of Meteorology. 2019. Australia’s National Weather Data. Australian Government, Bureau of Meteorology: Bureau of Meteorology, Australia. https://data.gov.au/dataset/4e21dea3-9b87-4610-94c7-15a8a77907ef.

Bureau of Transportation Statistics. 2018. Carrier on-Time Performance. 1200 New Jersey Avenue, SE Washington, DC 20590: U.S. Department of Transportation. https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236.

Chambers, John M, William S Cleveland, Beat Kleiner, and Paul A Tukey. 1983. Graphical Methods for Data Analysis. New York, NY: Chapman; Hall/CRC.

Chang, Winston, Joe Cheng, JJ Allaire, Yihui Xie, and Jonathan McPherson. 2019. Shiny: Web Application Framework for R. https://CRAN.R-project.org/package=shiny.

Cheng, Xiaoyue, Dianne Cook, and Heike Hofmann. 2015. “Visually Exploring Missing Values in Multivariable Data Using a Graphical User Interface.” Journal of Statistical Software 68 (6). https://doi.org/10.18637/jss.v068.i06.

City of Melbourne. 2017. Pedestrian Volume in Melbourne. City of Melbourne, Australia. http://www.pedestrian.melbourne.vic.gov.au.

Cleveland, William S. 1979. “Robust Locally Weighted Regression and Smoothing Scatterplots.” Journal of the American Statistical Association 74 (368). Taylor & Francis: 829–36. https://doi.org/10.1080/01621459.1979.10481038.

Cleveland, William S, and Robert McGill. 1984. “Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods.” Journal of the American Statistical Association 79 (387). Taylor & Francis: 531–54.

Codd, Edgar F. 1970. “A Relational Model of Data for Large Shared Data Banks.” Communications of the ACM 13 (6): 377–87.

Croissant, Yves, and Giovanni Millo. 2008. “Panel Data Econometrics in R: The Plm Package.” Journal of Statistical Software, Articles 27 (2): 1–43. https://doi.org/10.18637/jss.v027.i02.

Department of the Environment and Energy. 2018. Smart-Grid Smart-City Customer Trial Data. Australian Government, Department of the Environment; Energy: Department of the Environment; Energy, Australia. https://data.gov.au/dataset/4e21dea3-9b87-4610-94c7-15a8a77907ef.

Eddelbuettel, Dirk, and Leonardo Silvestri. 2018. Nanotime: Nanosecond-Resolution Time for R. https://CRAN.R-project.org/package=nanotime.

Freitas, Wilson. 2018. Bizdays: Business Days Calculations and Utilities. https://CRAN.R-project.org/package=bizdays.

Friedman, Daniel P., and Mitchell Wand. 2008. Essentials of Programming Languages, 3rd Edition. 3rd ed. The MIT Press.

Grolemund, Garrett, and Hadley Wickham. 2011. “Dates and Times Made Easy with Lubridate.” Journal of Statistical Software, Articles 40 (3): 1–25. https://doi.org/10.18637/jss.v040.i03.

Gschwandtner, Theresia, Wolfgang Aigner, Silvia Miksch, Johannes Gärtner, Simone Kriglstein, Margit Pohl, and Nik Suchy. 2014. “TimeCleanser: A Visual Analytics Approach for Data Cleansing of Time-Oriented Data.” In Proceedings of the 14th International Conference on Knowledge Technologies and Data-Driven Business - I-KNOW ’14, 1–8. Graz, Austria: ACM Press. https://doi.org/10.1145/2637748.2638423.

Gschwandtner, Theresia, Johannes Gärtner, Wolfgang Aigner, and Silvia Miksch. 2012. “A Taxonomy of Dirty Time-Oriented Data.” In Multidisciplinary Research and Practice for Information Systems, edited by Gerald Quirchmayr, Josef Basl, Ilsun You, Lida Xu, and Edgar Weippl, 58–72. Berlin, Heidelberg: Springer Berlin Heidelberg.

Hafen, Ryan. 2019. Geofacet: ’Ggplot2’ Faceting Utilities for Geographical Data. https://CRAN.R-project.org/package=geofacet.

Halldor Bjornsson, Tomas Johannesson &, and Icelandic Met. Office; Gabor Grothendieck. 2018. Stinepack: Stineman, a Consistently Well Behaved Method of Interpolation. https://CRAN.R-project.org/package=stinepack.

Henry, Lionel, and Hadley Wickham. 2019a. Purrr: Functional Programming Tools. https://CRAN.R-project.org/package=purrr.

———. 2019b. Rlang: Functions for Base Types and Core R and ’Tidyverse’ Features. https://CRAN.R-project.org/package=rlang.

———. 2019c. “Tidy Tidyverse Design Principles.” https://principles.tidyverse.org.

Hofmann, Heike. 2006. “Multivariate Categorical Data — Mosaic Plots.” In Graphics of Large Datasets: Visualizing a Million, 105–24. New York, NY: Springer New York. https://doi.org/10.1007/0-387-37977-0_5.

Hyndman, Rob J, and George Athanasopoulos. 2017. Forecasting: Principles and Practice. Melbourne, Australia: OTexts. OTexts.org/fpp2.

Hyndman, Rob, and Yeasmin Khandakar. 2008. “Automatic Time Series Forecasting: The Forecast Package for R.” Journal of Statistical Software, Articles 27 (3): 1–22. https://doi.org/10.18637/jss.v027.i03.

Hyndman, Rob, Alan Lee, Earo Wang, and Shanika Wickramasuriya. 2018. Hts: Hierarchical and Grouped Time Series. https://CRAN.R-project.org/package=hts.

Jacobs, Jay. 2017. Ggcal: Calendar Plot Using “Ggplot2”. https://github.com/jayjacobs/ggcal.

Kimball, Ralph, and Joe Caserta. 2011. The Data Warehouse Etl Toolkit: Practical Techniques for Extracting, Cleaning, Conforming, and Delivering Data. John Wiley & Sons.

Kothari, Aditya, and Ather. 2016. GgTimeSeries: Nicer Time Series Visualisations with Ggplot Syntax. https://github.com/Ather-Energy/ggTimeSeries.

Lam, Heidi, Tamara Munzner, and Robert Kincaid. 2007. “Overview Use in Multiple Visual Information Resolution Interfaces.” IEEE Transactions on Visualization and Computer Graphics 13 (6). IEEE: 1278–85.

Little, Roderick J. A. 1988. “A Test of Missing Completely at Random for Multivariate Data with Missing Values.” Journal of the American Statistical Association 83 (404). Taylor & Francis: 1198–1202. https://doi.org/10.1080/01621459.1988.10478722.

Long, Jacob A. 2019. Panelr: Regression Models and Utilities for Repeated Measures and Panel Data. https://CRAN.R-project.org/package=panelr.

McIlroy, Doug, E.N. Pinson, and B.A. Tague. 1978. “Unix Time-Sharing System Forward.” The Bell System Technical Journal, 1902–3. https://archive.org/details/bstj57-6-1899.

Moritz, Steffen, and Thomas Bartz-Beielstein. 2017. “imputeTS: Time Series Missing Value Imputation in R.” The R Journal 9 (1): 207–18. https://doi.org/10.32614/RJ-2017-009.

O’Hara-Wild, Mitchell, Rob Hyndman, and Earo Wang. 2019. Fable: Forecasting Models for Tidy Time Series. https://fable.tidyverts.org.

Pebesma, Edzer. 2018. “Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal 10 (1): 439–46. https://journal.r-project.org/archive/2018/RJ-2018-009/index.html.

R Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.

Ryan, Jeffrey A., and Joshua M. Ulrich. 2018. Xts: EXtensible Time Series. https://CRAN.R-project.org/package=xts.

SAS Institute Inc. 2018. SAS/STAT Software, Version 9.4. Cary, NC. http://www.sas.com/.

Sievert, Carson. 2018. Plotly for R. http://plotly-r.com.

Sparks, Adam, Jonathan Carroll, Dean Marchiori, Mark Padgham, Hugh Parsonage, and Keith Pembleton. 2018. Bomrang: Australian Government Bureau of Meteorology (Bom) Data from R. https://CRAN.R-project.org/package=bomrang.

StataCorp. 2017. Stata Statistical Software: Release 15. College Station, TX, United States: StataCorp LLC. https://www.stata.com.

Stineman, Russell W. 1980. “A Consistently Well Behaved Method of Interpolation.” Creative Computing 6 (7): 54–57.

Sutherland, Peter, Anthony Rossini, Thomas Lumley, Nicholas Lewin-Koh, Julie Dickerson, Zach Cox, and Dianne Cook. 2000. “Orca: A Visualization Toolkit for High-Dimensional Data.” Journal of Computational and Graphical Statistics 9 (3). Taylor & Francis: 509–29. https://doi.org/10.1080/10618600.2000.10474896.

Swayne, Deborah F., Dianne Cook, and Andreas Buja. 1998. “XGobi: Interactive Dynamic Data Visualization in the X Window System.” Journal of Computational and Graphical Statistics 7 (1). Taylor & Francis: 113–30. https://doi.org/10.1080/10618600.1998.10474764.

Swayne, Deborah F., Duncan Temple Lang, Andreas Buja, and Dianne Cook. 2003. “GGobi: Evolving from XGobi into an Extensible Framework for Interactive Data Visualization.” Computational Statistics & Data Analysis 43: 423–44.

Swayne, D F, and A Buja. 1998. “Missing Data in Interactive High-Dimensional Data Visualization.” Computational Statistics. researchgate.net, 1–8.

Tidyverse Team. 2019. “Tidy Evaluation.” https://tidyeval.tidyverse.org.

Tidyverts Team. 2019. “Tidy Tools for Time Series.” http://tidyverts.org.

Tierney, Nicholas J, and Dianne Cook. 2018. “Expanding Tidy Data Principles to Facilitate Missing Data Exploration, Visualization and Assessment of Imputations.”

Tufte, Edward R. 1983. The Visual Display of Quantitative Information. Graphics press Cheshire, CT.

Tukey, John W. 1977. Exploratory Data Analysis. Reading, Massachusetts: Addison-Wesley.

Unwin, Antony, George Hawkins, Heike Hofmann, and Bernd Siegl. 1996. “Interactive Graphics for Data Sets with Missing Values: MANET.” Journal of Computational and Graphical Statistics 5 (2). [American Statistical Association, Taylor & Francis, Ltd., Institute of Mathematical Statistics, Interface Foundation of America]: 113–22. http://www.jstor.org/stable/1390776.

Unwin, Antony, and Pedro Valero-Mora. 2018. “Ensemble Graphics.” Journal of Computational and Graphical Statistics 27 (1): 157–65. https://doi.org/10.1080/10618600.2017.1383264.

Ushey, Kevin. 2019. Renv: Project Environments. https://rstudio.github.io/renv.

Van Wijk, Jarke J., and Edward R. Van Selow. 1999. “Cluster and Calendar Based Visualization of Time Series Data.” In Information Visualization, 1999. INFOVIS 1999 Proceedings. IEEE Symposium on, 4–9. IEEE.

Vaughan, Davis, and Matt Dancho. 2018a. Furrr: Apply Mapping Functions in Parallel Using Futures. https://CRAN.R-project.org/package=furrr.

———. 2018b. Tibbletime: Time Aware Tibbles. https://CRAN.R-project.org/package=tibbletime.

Wang, Earo. 2019. Wanderer4melb: Shiny App for Wandering Around the Downtown Melbourne 2016. https://github.com/earowang/wanderer4melb.

Wang, Earo, Dianne Cook, and Rob J Hyndman. 2018. “Calendar-Based Graphics for Visualizing People’s Daily Schedules.”

———. 2019a. “A New Tidy Data Structure to Support Exploration and Modeling of Temporal Data.” Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2019.1695624.

Wang, Earo, Di Cook, and Rob Hyndman. 2019b. Sugrrants: Supporting Graphs for Analysing Time Series. https://CRAN.R-project.org/package=sugrrants.

———. 2019c. Tsibble: Tidy Temporal Data Frames and Tools. https://tsibble.tidyverts.org.

Welch, Greg, Gary Bishop, and others. 2006. “An Introduction to the Kalman Filter.” SIGGRAPH. https://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf.

Wickham, Hadley. 2009. Ggplot2: Elegant Graphics for Data Analysis. New York, NY: Springer-Verlag New York.

———. 2014. “Tidy Data.” Journal of Statistical Software 59 (10). Foundation for Open Access Statistics: 1–23.

———. 2017. Tidyverse: Easily Install and Load the ’Tidyverse’. https://CRAN.R-project.org/package=tidyverse.

———. 2018. Advanced R. 2nd ed. Chapman & Hall. https://adv-r.hadley.nz/.

Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, and Kara Woo. 2019. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://CRAN.R-project.org/package=ggplot2.

Wickham, Hadley, Romain François, Lionel Henry, and Kirill Müller. 2019. Dplyr: A Grammar of Data Manipulation.

Wickham, Hadley, and Garrett Grolemund. 2016. R for Data Science. O’Reilly Media. http://r4ds.had.co.nz/.

Wickham, Hadley, Lionel Henry, and Davis Vaughan. 2019. Vctrs: Vector Helpers. https://github.com/r-lib/vctrs.

Wickham, Hadley, Heike Hofmann, Charlotte Wickham, and Dianne Cook. 2012. “Glyph-Maps for Visually Exploring Temporal Patterns in Climate Data and Models.” Environmetrics 23 (5): 382–93.

Wickham, Hadley, Michael Lawrence, Dianne Cook, Andreas Buja, Heike Hofmann, and Deborah F Swayne. 2010. “The Plumbing of Interactive Graphics.” Computational Statistics, April, 1–7.

Wilkinson, Leland. 2005. The Grammar of Graphics (Statistics and Computing). Secaucus, NJ: Springer-Verlag New York, Inc.

Wong, Jeffrey. 2013. TimeProjection: Time Projections. https://CRAN.R-project.org/package=TimeProjection.

World Bank Group. 2019. World Development Indicators. The World Bank Group. https://databank.worldbank.org/source/world-development-indicators/.

World Health Organization. 2018. Tuberculosis Data. Block 3510, Jalan Teknokrat 6, 63000 Cyberjaya, Selangor, Malaysia: World Health Organization. http://www.who.int/tb/country/data/download/en/.

Xie, Yihui. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.name/knitr/.

———. 2016. Bookdown: Authoring Books and Technical Documents with R Markdown. Boca Raton, Florida: Chapman; Hall/CRC. https://github.com/rstudio/bookdown.

Xie, Yihui, J.J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.

Xie, Yihui, Heike Hofmann, and Xiaoyue Cheng. 2014. “Reactive Programming for Interactive Graphics.” Statistical Science 29 (2): 201–13.

Zeileis, Achim, and Gabor Grothendieck. 2005. “Zoo: S3 Infrastructure for Regular and Irregular Time Series.” Journal of Statistical Software 14 (6): 1–27. https://doi.org/10.18637/jss.v014.i06.