Rob J Hyndman

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George AthanasopoulosMonash UniversityVerified email at monash.edu
Ralph SnyderAdjuct Associate Professor, Monash UniversityVerified email at monash.edu
Kate Smith-MilesProfessor of Applied Mathematics, The University of MelbourneVerified email at unimelb.edu.au
Han Lin ShangDepartment of Actuarial Studies and Business Analytics, Macquarie UniversityVerified email at mq.edu.au
Keith OrdEmeritus Professor of Business Statistics, Georgetown UniversityVerified email at georgetown.edu
Christoph BergmeirUniversity of GranadaVerified email at monash.edu
Spyros MakridakisUniversity of Nicosia, Inst. For the Future (IFF), the Makridakis Open Forecast. Center MOFCVerified email at UNIC.ac.cy
Mitchell O'Hara-WildPhD Candidate, Monash UniversityVerified email at mitchelloharawild.com
Heather BoothAustralian National UniversityVerified email at anu.edu.au
Jan VerbesseltAssociate Professor, Wageningen UniversityVerified email at wur.nl
Bircan ErbasLa Trobe UniversityVerified email at latrobe.edu.au
Yeasmin KhandakarSenior Data Scientist, TransurbanVerified email at officeworks.com.au
Shanika WickramasuriyaLecturer, University of AucklandVerified email at auckland.ac.nz
Souhaib Ben TaiebAssociate Professor in Machine Learning, University of Mons, BelgiumVerified email at umons.ac.be
Fotios PetropoulosProfessor of Management Science, University of BathVerified email at bath.ac.uk
Dr. Farah YasmeenAssistant Professor Statistics Karachi UniversityVerified email at uok.edu.pk
Anastasios PanagiotelisAssociate Professor of Business Analytics, University of SydneyVerified email at sydney.edu.au
Darius CulvenorEnvironmental Sensing SystemsVerified email at sensingsystems.com.au
Yanfei KangSchool of Economics and Management, Beihang UniversityVerified email at buaa.edu.cn
Sevvandi KandanaarachchiCSIRO's Data61Verified email at data61.csiro.au

Rob J Hyndman

Professor of Statistics, Monash University

Verified email at monash.edu - Homepage

Forecasting Time series Statistics Exploratory data analysis Anomaly detection


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Forecasting: principles and practice RJ Hyndman, G Athanasopoulos OTexts, 2018	8496	2018
Forecasting methods and applications S Makridakis, SC Wheelwright, RJ Hyndman John Wiley & Sons, 1998	7728*	1998
Another look at measures of forecast accuracy RJ Hyndman, AB Koehler International journal of forecasting 22 (4), 679-688, 2006	6214	2006
Automatic time series forecasting: the forecast package for R RJ Hyndman, Y Khandakar Journal of Statistical Software, 2007	4880	2007
Forecasting with exponential smoothing: the state space approach RJ Hyndman, AB Koehler, JK Ord, RD Snyder Springer Verlag, 2008	2073	2008
Detecting trend and seasonal changes in satellite image time series J Verbesselt, R Hyndman, G Newnham, D Culvenor Remote sensing of Environment 114 (1), 106-115, 2010	1900	2010
forecast: Forecasting functions for time series and linear models RJ Hyndman	1788*	2021
25 years of time series forecasting JG De Gooijer, RJ Hyndman International journal of forecasting 22 (3), 443-473, 2006	1604	2006
Sample quantiles in statistical packages RJ Hyndman, Y Fan The American Statistician 50 (4), 361-365, 1996	1428	1996
A state space framework for automatic forecasting using exponential smoothing methods RJ Hyndman, AB Koehler, RD Snyder, S Grose International Journal of forecasting 18 (3), 439-454, 2002	1390	2002
Forecasting time series with complex seasonal patterns using exponential smoothing AM De Livera, RJ Hyndman, RD Snyder Journal of the American statistical association 106 (496), 1513-1527, 2011	1238	2011
Robust forecasting of mortality and fertility rates: A functional data approach RJ Hyndman, MS Ullah Computational Statistics and Data Analysis 51 (10), 4942-4956, 2007	951	2007
Probabilistic energy forecasting: Global energy forecasting competition 2014 and beyond T Hong, P Pinson, S Fan, H Zareipour, A Troccoli, RJ Hyndman International Journal of forecasting 32 (3), 896-913, 2016	944	2016
Characteristic-based clustering for time series data X Wang, K Smith, R Hyndman Data mining and knowledge Discovery 13, 335-364, 2006	864	2006
Phenological change detection while accounting for abrupt and gradual trends in satellite image time series J Verbesselt, R Hyndman, A Zeileis, D Culvenor Remote Sensing of Environment 114 (12), 2970-2980, 2010	847	2010
Computing and graphing highest density regions RJ Hyndman The American Statistician 50 (2), 120-126, 1996	843	1996
rmarkdown: Dynamic Documents for R J Allaire, Y Xie, J McPherson, J Luraschi, K Ushey, A Atkins, H Wickham, ... R package version 1 (11), 2018	720	2018
A note on the validity of cross-validation for evaluating autoregressive time series prediction C Bergmeir, RJ Hyndman, B Koo Computational Statistics & Data Analysis 120, 70-83, 2018	678	2018
Short-term load forecasting based on a semi-parametric additive model S Fan, RJ Hyndman IEEE transactions on power systems 27 (1), 134-141, 2011	601	2011
Optimal combination forecasts for hierarchical time series RJ Hyndman, RA Ahmed, G Athanasopoulos, HL Shang Computational statistics & data analysis 55 (9), 2579-2589, 2011	597	2011

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