Rob J Hyndman
Rob J Hyndman
Professor of Statistics, Monash University
Verified email at - Homepage
Cited by
Cited by
Forecasting: principles and practice
RJ Hyndman, G Athanasopoulos
OTexts, 2018
Forecasting methods and applications
S Makridakis, SC Wheelwright, RJ Hyndman
John Wiley & Sons, 1998
Another look at measures of forecast accuracy
RJ Hyndman, AB Koehler
International journal of forecasting 22 (4), 679-688, 2006
Automatic time series forecasting: the forecast package for R
RJ Hyndman, Y Khandakar
Journal of Statistical Software, 2007
Forecasting with exponential smoothing: the state space approach
RJ Hyndman, AB Koehler, JK Ord, RD Snyder
Springer Verlag, 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
forecast: Forecasting functions for time series and linear models
RJ Hyndman
25 years of time series forecasting
JG De Gooijer, RJ Hyndman
International journal of forecasting 22 (3), 443-473, 2006
Sample quantiles in statistical packages
RJ Hyndman, Y Fan
The American Statistician 50 (4), 361-365, 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
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
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
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
Characteristic-based clustering for time series data
X Wang, K Smith, R Hyndman
Data mining and knowledge Discovery 13, 335-364, 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
Computing and graphing highest density regions
RJ Hyndman
The American Statistician 50 (2), 120-126, 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
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
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
Optimal combination forecasts for hierarchical time series
RJ Hyndman, RA Ahmed, G Athanasopoulos, HL Shang
Computational statistics & data analysis 55 (9), 2579-2589, 2011
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