Rob J Hyndman - Google Scholar Citations

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George AthanasopoulosMonash UniversityVerified email at monash.edu
Ralph SnyderAdjuct Associate Professor, Monash UniversityVerified email at monash.edu
Han Lin ShangResearch School of Finance, Actuarial Studies & Statistics, Australian National UniversityVerified email at anu.edu.au
Keith OrdProfessor of Business Statistics, Georgetown UniversityVerified email at georgetown.edu
Kate Smith-MilesProfessor of Applied Mathematics, The University of MelbourneVerified email at unimelb.edu.au
Spyros MakridakisUniversity of Nicosia, Institute For the Future (IFF)Verified email at UNIC.ac.cy
Bircan ErbasLa Trobe UniversityVerified email at latrobe.edu.au
Muhammad AkramPhysics Division, PINSTECHVerified email at pinstech.org.pk
Christoph BergmeirMonash UniversityVerified email at monash.edu
Heather BoothAustralian National UniversityVerified email at anu.edu.au
Jan VerbesseltAssociate Professor, Wageningen UniversityVerified email at wur.nl
Darius CulvenorEnvironmental Sensing SystemsVerified email at sensingsystems.com.au
Fotios PetropoulosUniversity of BathVerified email at bath.ac.uk
Souhaib Ben TaiebAssociate Professor in Machine Learning, University of Mons, BelgiumVerified email at umons.ac.be
Michael AbramsonProfessor of clinical epidemiology, Monash UniversityVerified email at monash.edu
Dr Shahid UllahSenior Biostatistician and Senior Lecturer in Biostatistics, South Australian Health & MedicalVerified email at sahmri.com
Leonie TickleAssociate Professor in Actuarial Studies, Macquarie UniversityVerified email at mq.edu.au
Shyamali Chandrika DharmageProfessor of Epidemiology, Head of the Allergy and Lung Health Unit, University of MelbourneVerified email at unimelb.edu.au
Roman AhmedData Scientist, 460degreesVerified email at ambiata.com
Yanan FanAssociate Professor in Statistics, University of New South WalesVerified email at unsw.edu.au

Rob J Hyndman

Professor of Statistics, Monash University

Verified email at monash.edu - Homepage

Forecasting Time series Applied Statistics Machine learning Exploratory data analysis


Title	Cited by	Year
Forecasting methods and applications S Makridakis, SC Wheelwright, RJ Hyndman John Wiley & Sons, 1998	5324*	1998
Another look at measures of forecast accuracy RJ Hyndman, AB Koehler International journal of forecasting 22 (4), 679-688, 2006	2680	2006
Automatic time series forecasting: the forecast package for R RJ Hyndman, Y Khandakar Journal of Statistical Software, 2007	1748	2007
Forecasting: principles and practice RJ Hyndman, G Athanasopoulos OTexts, 2018	1502	2018
Forecasting with exponential smoothing: the state space approach RJ Hyndman, AB Koehler, JK Ord, RD Snyder Springer Verlag, 2008	913	2008
25 years of time series forecasting JG De Gooijer, RJ Hyndman International journal of forecasting 22 (3), 443-473, 2006	845	2006
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	831	2010
Sample quantiles in statistical packages RJ Hyndman, Y Fan The American Statistician 50 (4), 361-365, 1996	791	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	692	2002
forecast: Forecasting functions for time series and linear models RJ Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...	543*	2018
Computing and graphing highest density regions RJ Hyndman The American Statistician 50 (2), 120-126, 1996	521	1996
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	512	2007
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	411	2010
Characteristic-based clustering for time series data X Wang, K Smith, R Hyndman Data mining and knowledge Discovery 13 (3), 335-364, 2006	361	2006
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	358	2011
Estimating and visualizing conditional densities RJ Hyndman, DM Bashtannyk, GK Grunwald Journal of Computational and Graphical Statistics 5 (4), 315-336, 1996	352	1996
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	334	2011
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	307	2016
Density forecasting for long-term peak electricity demand RJ Hyndman, S Fan IEEE Transactions on Power Systems 25 (2), 1142-1153, 2009	251	2009
Time series data library RJ Hyndman http://robjhyndman.com/TSDL/, 2003	236*	2003

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