Rob J. Hyndman

According to our database1, Rob J. Hyndman authored at least 44 papers between 2004 and 2021.

Collaborative distances:



In proceedings 
PhD thesis 




Forecasting Swiss exports using Bayesian forecast reconciliation.
Eur. J. Oper. Res., 2021

A Look at the Evaluation Setup of the M5 Forecasting Competition.
CoRR, 2021

Detection of cybersecurity attacks through analysis of web browsing activities using principal component analysis.
CoRR, 2021

Monash Time Series Forecasting Archive.
CoRR, 2021

Manifold learning with approximate nearest neighbors.
CoRR, 2021

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics.
Stat. Anal. Data Min., 2020

Optimal non-negative forecast reconciliation.
Stat. Comput., 2020

On normalization and algorithm selection for unsupervised outlier detection.
Data Min. Knowl. Discov., 2020

Model selection in reconciling hierarchical time series.
CoRR, 2020

Forecasting for Social Good.
CoRR, 2020

Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality.
CoRR, 2020

Hierarchical forecast reconciliation with machine learning.
CoRR, 2020

Machine learning applications in time series hierarchical forecasting.
CoRR, 2019

Anomaly Detection in High Dimensional Data.
CoRR, 2019

Analysing Large Collections of Time Series (NII Shonan Meeting 2018-3).
NII Shonan Meet. Rep., 2018

Exploring the sources of uncertainty: Why does bagging for time series forecasting work?
Eur. J. Oper. Res., 2018

A note on the validity of cross-validation for evaluating autoregressive time series prediction.
Comput. Stat. Data Anal., 2018

A note on upper bounds for forecast-value-added relative to naïve forecasts.
J. Oper. Res. Soc., 2017

Dynamic algorithm selection for pareto optimal set approximation.
J. Glob. Optim., 2017

Forecasting with temporal hierarchies.
Eur. J. Oper. Res., 2017

Coherent Probabilistic Forecasts for Hierarchical Time Series.
Proceedings of the 34th International Conference on Machine Learning, 2017

Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression.
IEEE Trans. Smart Grid, 2016

Fast computation of reconciled forecasts for hierarchical and grouped time series.
Comput. Stat. Data Anal., 2016

On Sampling Methods for Costly Multi-Objective Black-Box Optimization.
Proceedings of the Advances in Stochastic and Deterministic Global Optimization., 2016

Large-Scale Unusual Time Series Detection.
Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

Efficient Identification of the Pareto Optimal Set.
Proceedings of the Learning and Intelligent Optimization, 2014

Boosting multi-step autoregressive forecasts.
Proceedings of the 31th International Conference on Machine Learning, 2014

Moving Averages.
Proceedings of the International Encyclopedia of Statistical Science, 2011

Forecasting: An Overview.
Proceedings of the International Encyclopedia of Statistical Science, 2011

Business Forecasting Methods.
Proceedings of the International Encyclopedia of Statistical Science, 2011

Nonparametric time series forecasting with dynamic updating.
Math. Comput. Simul., 2011

Improved interval estimation of long run response from a dynamic linear model: A highest density region approach.
Comput. Stat. Data Anal., 2011

Optimal combination forecasts for hierarchical time series.
Comput. Stat. Data Anal., 2011

Functionalization of microarray devices: Process optimization using a multiobjective PSO and multiresponse MARS modeling.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

Rule induction for forecasting method selection: Meta-learning the characteristics of univariate time series.
Neurocomputing, 2009

Forecasting time series with multiple seasonal patterns.
Eur. J. Oper. Res., 2008

Half-life estimation based on the bias-corrected bootstrap: A highest density region approach.
Comput. Stat. Data Anal., 2007

Robust forecasting of mortality and fertility rates: A functional data approach.
Comput. Stat. Data Anal., 2007

The accuracy of television network rating forecasts: The effects of data aggregation and alternative models.
Model. Assist. Stat. Appl., 2006

A note on the categorization of demand patterns.
J. Oper. Res. Soc., 2006

Characteristic-Based Clustering for Time Series Data.
Data Min. Knowl. Discov., 2006

A Bayesian approach to bandwidth selection for multivariate kernel density estimation.
Comput. Stat. Data Anal., 2006

Dimension Reduction for Clustering Time Series Using Global Characteristics.
Proceedings of the Computational Science, 2005

Exponential smoothing models: Means and variances for lead-time demand.
Eur. J. Oper. Res., 2004