Recent activity

20 Apr 2015:  
A note on the validity of cross-validation for evaluating time series prediction
[latexpage] Christoph Bergmeir, Rob J Hyndman, and Bonsoo Koo Abstract: One of the most widely used standard procedures for model evaluation in classification and regression is $K$-fold cross-validation (CV). However, when it comes to time serie...
4 Apr 2015:  
Discussion of “High-dimensional autocovariance matrices and optimal linear prediction”
Discussion of "High-dimensional autocovariance matrices and optimal linear prediction" by Timothy L. McMurry and Dimitris N. Politis. Electronic J Statistics (2015) 9, 792-796. Download pre-print Online article
23 Feb 2015:  
Visualization and forecasting of big time series data
Talk given at the ACEMS Big data workshop, QUT, 23 February 2015    
12 Jan 2015:  
Visualizing and forecasting big time series data
Institute of Statistical Science, Academia Sinica 時 間 2015/01/12 11:00 星期一 地 點 中研院-統計所 2F 交誼廳 備 註 茶 會:上午10:40統計所二樓交誼廳 Time series can often be naturally disaggregated in a hi...
24 Dec 2014:  
Bivariate data with ridges: two-dimensional smoothing of mortality rates
Alexander Dokumentov and Rob J Hyndman Abstract: In this article we explore some bivariate smoothing methods with partial differential regularizations designed to handle smooth bivariate surfaces with occasional ridges. We apply our technique t...
17 Dec 2014:  
MEFM package for R
The R package MEFM includes a set of tools for implementing the Monash Electricity Forecasting Model based on the paper by Hyndman and Fan (2010). The package requires the following data as input: half-hourly/hourly electricity demands; half-hourl...
21 Oct 2014:  
Optimally reconciling forecasts in a hierarchy
Rob J Hyndman and George Athanasopoulos Foresight (Fall, 2014). pp.42-48. This is an introduction to our approach to forecast reconciliation without using any matrices. The original research is available here: Hyndman, Ahmed, Athanasopoulos...
16 Sep 2014:  
Forecasting: principles and practice (UWA course)
Workshop to be held on 23-25 September 2014. Venue: The University Club, University of Western Australia, Nedlands WA. Requirements: a laptop with R installed, along with the fpp package and its dependencies. We will also use the hts and vars p...
1 Sep 2014:  
Outdoor fungal spores are associated with child asthma hospitalisations - a case-crossover study
Rachel Tham, Shyamali Dharmage, Philip Taylor, Ed Newbigin, Mimi L.K. Tang, Don Vicendese, Rob J. Hyndman, Michael J. Abramson and Bircan Erbas European Respiratory Journal (2014), 44(Suppl 58). Abstract Introduction Asthma can be exac...
1 Aug 2014:  
Efficient identification of the Pareto optimal set
Ingrida Steponavičė1, Rob J. Hyndman2, Kate Smith-Miles1 and Laura Villanova3 School of Mathematical Sciences, Monash University, Clayton, Australia Department of Econometrics & Business Statistics, Monash University, Clayton, Australia ...
14 Jun 2014:  
Fast computation of reconciled forecasts in hierarchical and grouped time series
Talk to be given at the International Symposium on Forecasting, Rotterdam. 1 July 2014.
8 Jun 2014:  
Functional time series with applications in demography
This is a short course I am giving at Humboldt University, Berlin, 24-25 June 2014. Venue: LvB Library, Room 401, Spandauerstr. 1, 10178 Berlin Time: 24 June 2014, 09:30 - 12:30 and 14:00 - 17:00 25 June 2014, 09:30 - 11:30 Abstract: Fu...
5 Jun 2014:  
Challenges in forecasting peak electricity demand
I am giving a two-part seminar at the Energy Forum, Valais/Wallis, Switzerland, on 17 June 2014. (English brochure) Abstract: Electricity demand forecasting plays an important role in short-term load allocation and long-term planning for future g...
5 Jun 2014:  
Low-dimensional decomposition, smoothing and forecasting of sparse functional data
Alexander Dokumentov and Rob J Hyndman Department of Econometrics & Business Statistics, Monash University, Australia Abstract: We propose a new generic method ROPES (Regularized Optimization for Prediction and Estimation with Sparse data) for de...
5 Jun 2014:  
Fast computation of reconciled forecasts for hierarchical and grouped time series
Rob J Hyndman1, Alan Lee2 & Earo Wang1 Department of Econometrics and Business Statistics, Monash University, Australia University of Auckland, New Zealand. Abstract We describe some fast algorithms for reconciling large collections of time...
29 May 2014:  
State space models
A one-day workshop for the Australian Bureau of Statistics, 30 May 2014 Exponential smoothing Slides R examples Lab session Solutions to lab session Structural models Slides R examples Lab session Solutions to lab sessio...
24 May 2014:  
Common functional principal component models for mortality forecasting
Rob J Hyndman1 and Farah Yasmeen2 Monash University, Australia. University of Karachi, Pakistan. Contributions in infinite-dimensional statistics and related topics Chapter 29, pages 161-166. Abstract: We explore models for forecasting g...
22 May 2014:  
Monash Electricity Forecasting Model
Rob J Hyndman and Shu Fan The model we developed for peak electricity demand forecasting in Hyndman and Fan (2010) is now widely used in practice around Australia, and has undergone many improvements and developments. This document describes the c...
8 May 2014:  
forecast package for R
The forecast package for R provides methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling. It also includes a handful of data sets from the...
2 May 2014:  
“Facts” may still be artefacts, since models can make unrealistic assumptions: statistical methods for the estimation of invasion lag-phases from herbarium data
Rob J. Hyndman1, Mohsen B. Mesgaran2 and Roger D. Cousens2 Department of Econometrics & Business Statistics, Monash University, VIC 3800, Australia Department of Resource Management & Geography, The University of Melbourne, Victoria 3010, Austral...
9 Apr 2014:  
hts package for R
The hts package provides methods for analysing and forecasting hierarchical time series. [iframe http://cran.r-project.org/web/packages/hts/index.html 600 900]
1 Apr 2014:  
A gradient boosting approach to the Kaggle load forecasting competition
International Journal of Forecasting (2014), 30(2), 382–394. Souhaib Ben Taieb (1) and Rob J Hyndman (2) (1) Machine Learning Group, Department of Computer Science, Université Libre de Bruxelles (2) Depart­ment of Eco­no­met­rics &...
31 Mar 2014:  
Measuring forecast accuracy
This is a chapter for a new book on forecasting in business.
21 Mar 2014:  
Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation
Christoph Bergmeir1, Rob J Hyndman2, José M Benítez1 Department of Computer Science and Artificial Intelligence, University of Granada, Spain. Department of Econometrics and Business Statistics, Monash University, Australia. Abstract: E...
13 Feb 2014:  
Automatic time series forecasting
Talk presented at the conference "New Trends on Intelligent Systems and Soft Computing 2014", University of Granada, Spain. 13-14 February 2014. Abstract Many applications require a large number of time series to be forecast completely automatica...