Rob J. Hyndman

According to our database1, Rob J. Hyndman authored at least 33 papers between 2004 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

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

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

Anomaly Detection in High Dimensional Data.
CoRR, 2019

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics.
CoRR, 2019

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

2017
A note on upper bounds for forecast-value-added relative to naïve forecasts.
JORS, 2017

Dynamic algorithm selection for pareto optimal set approximation.
J. Global Optimization, 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

2016
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

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

2014
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

2011
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.
Mathematics and Computers in Simulation, 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

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

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

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

2007
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

2006
The accuracy of television network rating forecasts: The effects of data aggregation and alternative models.
MASA, 2006

A note on the categorization of demand patterns.
JORS, 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

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

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


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