Rob J. Hyndman: Difference between revisions
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'''Robin John Hyndman''' |
'''Robin John Hyndman''' (born 2 May 1967) is an Australian [[statistician]] known for his work on [[forecasting]] and [[time series]]. He is Professor of Statistics at [[Monash University]]<ref name=Monash>{{Cite web |
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|title = Rob Hyndman - Monash University |
|title = Rob Hyndman - Monash University |
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|publisher = [[Monash University]] |
|publisher = [[Monash University]] |
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Revision as of 13:10, 6 October 2024
Rob J. Hyndman | |
|---|---|
| Born | 2 May 1967 |
| Nationality | Australian |
| Alma mater | University of Melbourne |
| Known for | Forecasting research |
| Awards | Moran Medal (2007) Pitman Medal (2021) |
| Scientific career | |
| Fields | Statistics |
| Institutions | Monash University |
| Thesis | Continuous-Time Threshold Autoregressive Modelling (1992) |
| Doctoral advisor | Peter J. Brockwell Gary K. Grunwald |
| Website | robjhyndman |
Robin John Hyndman (born 2 May 1967) is an Australian statistician known for his work on forecasting and time series. He is Professor of Statistics at Monash University[1] and was Editor-in-Chief of the International Journal of Forecasting from 2005–2018.[2] In 2007 he won the Moran Medal from the Australian Academy of Science for his contributions to statistical research.[3] In 2021 he won the Pitman Medal from the Statistical Society of Australia.[4]
Hyndman is co-creator and proponent of the scale-independent forecast error measurement metric mean absolute scaled error (MASE).[5] Common metrics of forecast error, such as mean absolute error, geometric mean absolute error, and mean squared error, have shortcomings related to dependence on scale of data and/or handling zeros and negative values within the data. Hyndman's MASE metric resolves these and can be used under any forecast generation method.[6] It allows for comparison between models due to its scale-free property.
Hyndman studied statistics and mathematics at the University of Melbourne, where he earned a Bachelor of Science with first class honours and a PhD.[1] He was elected Fellow of the Academy of the Social Sciences in Australia in 2020,[7] and Fellow of the Australian Academy of Science in 2021.[8]
Major books
- Makridakis, S., Wheelwright, S., and Hyndman, R.J. (1998) Forecasting: methods and applications, Wiley.
- Hyndman, R.J., Koehler, A.B., Ord, J.K., and Snyder, R.D. (2008) Forecasting with exponential smoothing: the state space approach, Springer.
- Hyndman, R.J., and Athanasopoulos, G. (2014) Forecasting: principles and practice, OTexts. (self-published)
- Hyndman, R.J. (2015) Unbelievable, CreateSpace. (self-published)
References
- ^ a b "Rob Hyndman - Monash University". Monash University. Archived from the original on 31 December 2021. Retrieved 23 April 2018.
- ^ "Editors". International Journal of Forecasting. Archived from the original on 12 May 2010. Retrieved 20 May 2010.
- ^ "Rob Hyndman awarded with prestigious Moran Medal". Monash University Business and Economics. Archived from the original on 14 September 2010. Retrieved 20 May 2010.
- ^ "Pitman Medal Recipients". Statistical Society of Australia. Archived from the original on 5 March 2022. Retrieved 28 July 2021.
- ^ Hyndman, Rob J.; Koehler, Anne B. (1 October 2006). "Another look at measures of forecast accuracy" (PDF). International Journal of Forecasting. 22 (4): 679–688. doi:10.1016/j.ijforecast.2006.03.001. ISSN 0169-2070. S2CID 15947215. Retrieved 5 April 2022.
- ^ Hyndman, Rob. (2006). "Another Look at Forecast Accuracy Metrics for Intermittent Demand". Foresight: The International Journal of Applied Forecasting. 4. 43–46.
- ^ "Academy Fellow: Professor Rob Hyndman FASSA". Academy of the Social Sciences in Australia. Archived from the original on 21 March 2022. Retrieved 4 December 2020.
- ^ "Rob Hyndman". Australian Academy of Science. Archived from the original on 31 December 2021. Retrieved 5 July 2021.
External links
- Professor Rob J Hyndman Personal website
- Rob J. Hyndman at the Mathematics Genealogy Project
