Rob J. Hyndman

62 papers A* 2B 1Misc 1Journal 50Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Distortion Corrected Kernel Density Estimator on Riemannian Manifolds. J. Comput. Graph. Stat. Fan Cheng, Rob J. Hyndman, Anastasios Panagiotelis
2025	J	`jnl`	Forecasting interrupted time series. J. Oper. Res. Soc. Rob J. Hyndman, Bahman Rostami Tabar
2025	J	`jnl`	Optimal forecast reconciliation with time series selection. Eur. J. Oper. Res. Xiaoqian Wang, Rob J. Hyndman, Shanika L. Wickramasuriya
2025	J	`jnl`	ggtime: A Grammar of Temporal Graphics. CoRR Cynthia A. Huang, Mitchell O'Hara-Wild, Rob J. Hyndman, Matthew Kay
2024	—	`conf`	Extreme Value Modelling of Feature Residuals for Anomaly Detection in Dynamic Graphs. ISCMI Sevvandi Kandanaarachchi, Conrad Sanderson, Rob J. Hyndman
2024	J	`jnl`	Extreme Value Modelling of Feature Residuals for Anomaly Detection in Dynamic Graphs. CoRR Sevvandi Kandanaarachchi, Conrad Sanderson, Rob J. Hyndman
2023	J	`jnl`	Probabilistic forecast reconciliation: Properties, evaluation and score optimisation. Eur. J. Oper. Res. Anastasios Panagiotelis, Puwasala Gamakumara, George Athanasopoulos, Rob J. Hyndman
2022	J	`jnl`	Anomaly detection in dynamic networks. CoRR Sevvandi Kandanaarachchi, Rob J. Hyndman
2022	J	`jnl`	Fast Forecast Reconciliation Using Linear Models. J. Comput. Graph. Stat. Mahsa Ashouri, Rob J. Hyndman, Galit Shmueli
2022	J	`jnl`	Leave-One-Out Kernel Density Estimates for Outlier Detection. J. Comput. Graph. Stat. Sevvandi Kandanaarachchi, Rob J. Hyndman
2022	J	`jnl`	Model selection in reconciling hierarchical time series. Mach. Learn. Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir
2022	J	`jnl`	Visualizing Probability Distributions Across Bivariate Cyclic Temporal Granularities. J. Comput. Graph. Stat. Sayani Gupta, Rob J. Hyndman, Dianne Cook, Antony Unwin
2021	J	`jnl`	A Look at the Evaluation Setup of the M5 Forecasting Competition. CoRR Hansika Hewamalage, Pablo Montero-Manso, Christoph Bergmeir, Rob J. Hyndman
2021	J	`jnl`	Anomaly Detection in High-Dimensional Data. J. Comput. Graph. Stat. Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
2021	J	`jnl`	Detection of cybersecurity attacks through analysis of web browsing activities using principal component analysis. CoRR Insha Ullah, Kerrie L. Mengersen, Rob J. Hyndman, James M. McGree
2021	J	`jnl`	Dimension Reduction for Outlier Detection Using DOBIN. J. Comput. Graph. Stat. Sevvandi Kandanaarachchi, Rob J. Hyndman
2021	J	`jnl`	Forecasting Swiss exports using Bayesian forecast reconciliation. Eur. J. Oper. Res. Florian Eckert, Rob J. Hyndman, Anastasios Panagiotelis
2021	J	`jnl`	Hierarchical forecast reconciliation with machine learning. Appl. Soft Comput. Evangelos Spiliotis, Mahdi Abolghasemi, Rob J. Hyndman, Fotios Petropoulos, Vassilios Assimakopoulos
2021	J	`jnl`	LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts. CoRR Dilini Rajapaksha, Christoph Bergmeir, Rob J. Hyndman
2021	J	`jnl`	Manifold learning with approximate nearest neighbors. CoRR Fan Cheng, Rob J. Hyndman, Anastasios Panagiotelis
2021	—	`conf`	Monash Time Series Forecasting Archive. NeurIPS Datasets and Benchmarks Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Rob J. Hyndman, Pablo Montero-Manso
2021	J	`jnl`	Monash Time Series Forecasting Archive. CoRR Rakshitha Godahewa, Christoph Bergmeir, Geoffrey I. Webb, Rob J. Hyndman, Pablo Montero-Manso
2020	J	`jnl`	Forecasting for Social Good. CoRR Bahman Rostami Tabar, Mohammad M. Ali, Tao Hong, Rob J. Hyndman, Michael D. Porter, Aris A. Syntetos
2020	J	`jnl`	GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. Stat. Anal. Data Min. Yanfei Kang, Rob J. Hyndman, Feng Li
2020	J	`jnl`	Hierarchical forecast reconciliation with machine learning. CoRR Evangelos Spiliotis, Mahdi Abolghasemi, Rob J. Hyndman, Fotios Petropoulos, Vassilios Assimakopoulos
2020	J	`jnl`	Model selection in reconciling hierarchical time series. CoRR Mahdi Abolghasemi, Rob J. Hyndman, Evangelos Spiliotis, Christoph Bergmeir
2020	J	`jnl`	On normalization and algorithm selection for unsupervised outlier detection. Data Min. Knowl. Discov. Sevvandi Kandanaarachchi, Mario A. Muñoz, Rob J. Hyndman, Kate Smith-Miles
2020	J	`jnl`	Optimal non-negative forecast reconciliation. Stat. Comput. Shanika L. Wickramasuriya, Berwin A. Turlach, Rob J. Hyndman
2020	J	`jnl`	Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality. CoRR Pablo Montero-Manso, Rob J. Hyndman
2019	J	`jnl`	Anomaly Detection in High Dimensional Data. CoRR Priyanga Dilini Talagala, Rob J. Hyndman, Kate Smith-Miles
2019	J	`jnl`	GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. CoRR Yanfei Kang, Rob J. Hyndman, Feng Li
2019	J	`jnl`	Machine learning applications in time series hierarchical forecasting. CoRR Mahdi Abolghasemi, Rob J. Hyndman, Garth Tarr, Christoph Bergmeir
2018	J	`jnl`	A note on the validity of cross-validation for evaluating autoregressive time series prediction. Comput. Stat. Data Anal. Christoph Bergmeir, Rob J. Hyndman, Bonsoo Koo
2018	J	`jnl`	Analysing Large Collections of Time Series (NII Shonan Meeting 2018-3). NII Shonan Meet. Rep. Anne Driemel, Rob J. Hyndman, Galit Shmueli
2018	J	`jnl`	Exploring the sources of uncertainty: Why does bagging for time series forecasting work? Eur. J. Oper. Res. Fotios Petropoulos, Rob J. Hyndman, Christoph Bergmeir
2017	J	`jnl`	A note on upper bounds for forecast-value-added relative to naïve forecasts. J. Oper. Res. Soc. Paul Goodwin, Fotios Petropoulos, Rob J. Hyndman
2017	A*	`conf`	Coherent Probabilistic Forecasts for Hierarchical Time Series. ICML Souhaib Ben Taieb, James W. Taylor, Rob J. Hyndman
2017	J	`jnl`	Dynamic algorithm selection for pareto optimal set approximation. J. Glob. Optim. Ingrida Steponavice, Rob J. Hyndman, Kate Smith-Miles, Laura Villanova
2017	J	`jnl`	Forecasting with temporal hierarchies. Eur. J. Oper. Res. George Athanasopoulos, Rob J. Hyndman, Nikolaos Kourentzes, Fotios Petropoulos
2016	J	`jnl`	Fast computation of reconciled forecasts for hierarchical and grouped time series. Comput. Stat. Data Anal. Rob J. Hyndman, Alan J. Lee, Earo Wang
2016	J	`jnl`	Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression. IEEE Trans. Smart Grid Souhaib Ben Taieb, Raphaël Huser, Rob J. Hyndman, Marc G. Genton
2016	—	`ch.`	On Sampling Methods for Costly Multi-Objective Black-Box Optimization. Advances in Stochastic and Deterministic Global Optimization Ingrida Steponavice, Mojdeh Shirazi-Manesh, Rob J. Hyndman, Kate Smith-Miles, Laura Villanova
2015	—	`conf`	Large-Scale Unusual Time Series Detection. ICDM Workshops Rob J. Hyndman, Earo Wang, Nikolay Laptev
2014	A*	`conf`	Boosting multi-step autoregressive forecasts. ICML Souhaib Ben Taieb, Rob J. Hyndman
2014	—	`conf`	Efficient Identification of the Pareto Optimal Set. LION Ingrida Steponavice, Rob J. Hyndman, Kate Smith-Miles, Laura Villanova
2011	—	`ch.`	Business Forecasting Methods. International Encyclopedia of Statistical Science Rob J. Hyndman
2011	—	`ch.`	Forecasting: An Overview. International Encyclopedia of Statistical Science Rob J. Hyndman
2011	J	`jnl`	Improved interval estimation of long run response from a dynamic linear model: A highest density region approach. Comput. Stat. Data Anal. Jae H. Kim, Iain Fraser, Rob J. Hyndman
2011	—	`ch.`	Moving Averages. International Encyclopedia of Statistical Science Rob J. Hyndman
2011	J	`jnl`	Nonparametric time series forecasting with dynamic updating. Math. Comput. Simul. Han Lin Shang, Rob J. Hyndman
2011	J	`jnl`	Optimal combination forecasts for hierarchical time series. Comput. Stat. Data Anal. Rob J. Hyndman, Roman A. Ahmed, George Athanasopoulos, Han Lin Shang
2010	B	`conf`	Functionalization of microarray devices: Process optimization using a multiobjective PSO and multiresponse MARS modeling. IEEE Congress on Evolutionary Computation Laura Villanova, Paolo Falcaro, Davide Carta, Irene Poli, Rob J. Hyndman, Kate Smith-Miles
2009	J	`jnl`	Rule induction for forecasting method selection: Meta-learning the characteristics of univariate time series. Neurocomputing Xiaozhe Wang, Kate Amanda Smith-Miles, Rob J. Hyndman
2008	J	`jnl`	Forecasting time series with multiple seasonal patterns. Eur. J. Oper. Res. Phillip G. Gould, Anne B. Koehler, J. Keith Ord, Ralph D. Snyder, Rob J. Hyndman, Farshid Vahid-Araghi
2007	J	`jnl`	Half-life estimation based on the bias-corrected bootstrap: A highest density region approach. Comput. Stat. Data Anal. Jae H. Kim, Param Silvapulle, Rob J. Hyndman
2007	J	`jnl`	Robust forecasting of mortality and fertility rates: A functional data approach. Comput. Stat. Data Anal. Rob J. Hyndman, Md. Shahid Ullah
2006	J	`jnl`	A Bayesian approach to bandwidth selection for multivariate kernel density estimation. Comput. Stat. Data Anal. Xibin Zhang, Maxwell L. King, Rob J. Hyndman
2006	J	`jnl`	A note on the categorization of demand patterns. J. Oper. Res. Soc. A. V. Kostenko, Rob J. Hyndman
2006	J	`jnl`	Characteristic-Based Clustering for Time Series Data. Data Min. Knowl. Discov. Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
2006	J	`jnl`	The accuracy of television network rating forecasts: The effects of data aggregation and alternative models. Model. Assist. Stat. Appl. Denny Meyer, Rob J. Hyndman
2005	Misc	`conf`	Dimension Reduction for Clustering Time Series Using Global Characteristics. International Conference on Computational Science (3) Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
2004	J	`jnl`	Exponential smoothing models: Means and variances for lead-time demand. Eur. J. Oper. Res. Ralph D. Snyder, Anne B. Koehler, Rob J. Hyndman, J. Keith Ord