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Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman

Abstract:
Many applications require forecasts for a hierarchy comprising a set of time series along with aggregates of subsets of these series. Although forecasts can be produced independently for each series in the hierarchy, typically this does not lead to coherent forecasts — the property that forecasts add up appropriately across the hierarchy. State-of-the-art hierarchical forecasting methods usually reconcile these independently generated forecasts to satisfy the aggregation constraints. A fundamental limitation of prior research is that it has looked only at the problem of forecasting the mean of each time series. We consider the situation where probabilistic forecasts are needed for each series in the hierarchy. We define forecast coherency in this setting, and propose an algorithm to compute predictive distributions for each series in the hierarchy. Our algorithm has the advantage of synthesizing information from different levels in the hierarchy through a sparse forecast combination and a probabilistic hierarchical aggregation. We evaluate the accuracy of our forecasting algorithm on both simulated data and large-scale electricity smart meter data. The results show consistent performance gains compared to state-of-the art methods

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  Tag: hierarchical time series

27 posts
March 7th, 2017

Coherent Probabilistic Forecasts for Hierarchical Time Series

Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman Abstract: Many applications require forecasts for a hierarchy comprising a set […]

February 28th, 2017

Forecasting with temporal hierarchies

George Athanasopoulosa, Rob J. Hyndmana, Nikolaos Kourentzesb, Fotios Petropoulosc a Department of Econometrics and Business Statistics, Monash University, Australia b […]

January 1st, 2017

Grouped functional time series forecasting: an application to age-specific mortality rates

Han Lin Shang and Rob J Hyndman Journal of Computational and Graphical Statistics (2017) to appear. Abstract Age-specific mortality rates […]

October 13th, 2016

Reconciling forecasts: the hts and thief packages

Talk given at eRum2016, Poznań, Poland.  

September 15th, 2016

Forecasting large collections of related time series

Talk given at the German Statistical Week, Augsburg, 15 September 2016

August 22nd, 2016

thief package for R

The thief package provides tools for Temporal Hierarchical Forecasting. The methods are described in Forecasting with temporal hierarchies, co-authored with […]

January 1st, 2016

Fast computation of reconciled forecasts for hierarchical and grouped time series

By Rob J Hyndman, Ala Lee & Earo Wang

November 26th, 2015

Forecasting hierarchical and grouped time series through trace minimization

Shanika L Wickramasuriya, George Athanasopoulos, Rob J Hyndman Department of Econometrics and Business Statistics, Monash University   Abstract Large collections […]

February 23rd, 2015

Visualization and forecasting of big time series data

Talk given at the ACEMS Big data workshop, QUT.

January 12th, 2015

Visualizing and forecasting big time series data

Talk given at the Institute of Statistical Science, Academia Sinica, Taipei, Taiwan.

October 21st, 2014

Optimally reconciling forecasts in a hierarchy

By Rob J Hyndman and George Athanasopoulos

Foresight (Fall, 2014). pp.42-48.

September 23rd, 2014

Forecasting: principles and practice (UWA course)

Workshop held at UWA on 23-25 September 2014.

July 1st, 2014

Fast computation of reconciled forecasts in hierarchical and grouped time series

Talk given at the International Symposium on Forecasting, Rotterdam.

April 9th, 2014

hts package for R

The hts package provides methods for analysing and forecasting hierarchical time series.

October 10th, 2013

Forecasting hierarchical time series

Talk given at University of Sydney today.

July 4th, 2013

R tools for hierarchical time series

Talk given at EURO/INFORMS, Rome, 1 July 2013 And at UseR! 2013, Albacete, Spain, 10 July 2013.

May 7th, 2013

hts: An R package for forecasting hierarchical or grouped time series

Rob J Hyndman, George Athanasopoulos and Han Lin Shang The new version of the hts package (v3.01) has a vignette.

June 19th, 2012

Advances in automatic time series forecasting

Invited talk, Australian Statistical Conference, Adelaide, 10 July 2012. COMPSTAT 2012, Cyprus, 29 August 2012. Seminar, Lancaster University, 10 September […]

March 16th, 2011

Optimal combination forecasts for hierarchical time series

Rob J. Hyndman1, Roman A. Ahmed2, George Athanasopoulos1 and Han L Shang1 Department of Econometrics and Business Statistics, Monash University, […]

January 17th, 2009

Hierarchical forecasts for Australian domestic tourism

George Athanasopoulos1 , Roman A. Ahmed1 and Rob J. Hyndman1 International Journal of Forecasting (2009), 25(1), 146-166. Department of Econometrics […]

June 20th, 2006

Optimal combination forecasts for hierarchical time series

When: June 2006 Where: International Symposium on Forecasting, Santander, Spain Speakers: Rob J Hyndman and Roman A. Ahmed Slides (3.0Mb)