Rob J. Hyndman

Orcid: 0000-0002-2140-5352

According to our database1, Rob J. Hyndman authored at least 116 papers between 2004 and 2024.

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Bibliography

2024
Extreme Value Modelling of Feature Residuals for Anomaly Detection in Dynamic Graphs.
CoRR, 2024

2023
Probabilistic forecast reconciliation: Properties, evaluation and score optimisation.
Eur. J. Oper. Res., 2023

2022
Extended Wikipedia Web Traffic Daily Dataset (without Missing Values).
Dataset, November, 2022

Extended Wikipedia Web Traffic Daily Dataset (with Missing Values).
Dataset, November, 2022

Leave-One-Out Kernel Density Estimates for Outlier Detection.
J. Comput. Graph. Stat., January, 2022

Model selection in reconciling hierarchical time series.
Mach. Learn., 2022

Visualizing Probability Distributions Across Bivariate Cyclic Temporal Granularities.
J. Comput. Graph. Stat., 2022

Fast Forecast Reconciliation Using Linear Models.
J. Comput. Graph. Stat., 2022

Anomaly detection in dynamic networks.
CoRR, 2022

2021

Temperature Rain Dataset without Missing Values.
Dataset, July, 2021

Temperature Rain Dataset with Missing Values.
Dataset, July, 2021

Vehicle Trips Dataset without Missing Values.
Dataset, July, 2021

Vehicle Trips Dataset with Missing Values.
Dataset, July, 2021

Rideshare Dataset without Missing Values.
Dataset, July, 2021

Rideshare Dataset with Missing Values.
Dataset, July, 2021

Bitcoin Dataset without Missing Values.
Dataset, July, 2021

Bitcoin Dataset with Missing Values.
Dataset, July, 2021

COVID-19 Mobility Dataset (without Missing Values).
Dataset, April, 2021

COVID-19 Mobility Dataset (with Missing Values).
Dataset, April, 2021

Australian Electricity Demand Dataset.
Dataset, April, 2021

Anomaly Detection in High-Dimensional Data.
J. Comput. Graph. Stat., 2021

Dimension Reduction for Outlier Detection Using DOBIN.
J. Comput. Graph. Stat., 2021

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

LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts.
CoRR, 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

Manifold learning with approximate nearest neighbors.
CoRR, 2021

Hierarchical forecast reconciliation with machine learning.
Appl. Soft Comput., 2021

Monash Time Series Forecasting Archive.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020



Car Parts Dataset (with Missing Values).
Dataset, August, 2020

Car Parts Dataset (without Missing Values).
Dataset, August, 2020



Wind Power Dataset (4 Seconds Observations).
Dataset, August, 2020

Solar Power Dataset (4 Seconds Observations).
Dataset, August, 2020

Wind Farms Dataset (with Missing Values).
Dataset, August, 2020

Wind Farms Dataset (without Missing Values).
Dataset, August, 2020




Solar Dataset (10 Minutes Observations).
Dataset, June, 2020






NN5 Daily Dataset (without Missing Values).
Dataset, June, 2020

NN5 Daily Dataset (with Missing Values).
Dataset, June, 2020




Kaggle Wikipedia Web Traffic Daily Dataset (with Missing Values).
Dataset, June, 2020

Kaggle Wikipedia Web Traffic Daily Dataset (without Missing Values).
Dataset, June, 2020

London Smart Meters Dataset (with Missing Values).
Dataset, June, 2020

Electricity Demand (Elecdemand) Dataset.
Dataset, June, 2020

Saugeen River Flow (SaugeenDay) Dataset.
Dataset, June, 2020



KDD Cup Dataset (without Missing Values).
Dataset, June, 2020

KDD Cup Dataset (with Missing Values).
Dataset, June, 2020

Kaggle Wikipedia Web Traffic Weekly Dataset.
Dataset, June, 2020

Melbourne Pedestrian Counts Dataset.
Dataset, June, 2020


London Smart Meters Dataset (without Missing Values).
Dataset, June, 2020











Sunspot Daily Dataset (with Missing Values).
Dataset, June, 2020

Sunspot Daily Dataset (without Missing Values).
Dataset, June, 2020

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

Forecasting for Social Good.
CoRR, 2020

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

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

2018
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

2017
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

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.
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

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.
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

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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