Rob Hyndman

Professor of Statistics (Statistics not elsewhere classified)

Clayton, Victoria, Australia

http://robjhyndman.com

Publications

  • Forecasting electricity demand in Australian National Electricity Market
  • Coherent probabilistic forecasts for hierarchical time series
  • Boosting multi-step autoregressive forecasts
  • Forecasts of COPD mortality in Australia: 2006-2025
  • Forecasting time series with complex seasonal patterns using exponential smoothing
  • Visualizing Big Energy Data: Solutions for This Crucial Component of Data Analysis
  • STR: Seasonal-Trend Decomposition Using Regression
  • Optimal non-negative forecast reconciliation
  • On normalization and algorithm selection for unsupervised outlier detection
  • Fast computation of reconciled forecasts for hierarchical and grouped time series
  • A Feature‐Based Procedure for Detecting Technical Outliers in Water‐Quality Data From In Situ Sensors
  • Change to the IJF editors
  • Corrigendum to: "Hierarchical forecasts for Australian domestic tourism" [International journal of forecasting 25 (2009) 146-166]
  • Do human rhinovirus infections and food allergy modify grass pollen-induced asthma hospital admissions in children?
  • Statistical issues with using herbarium data for the estimation of invasion lag-phases
  • New IJF editors
  • On sampling methods for costly multi-objective black-box optimization
  • Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation
  • Large-Scale Unusual Time Series Detection
  • Handgun acquisitions in California after two Mass shootings
  • Forecasting uncertainty in electricity smart meter data by boosting additive quantile regression
  • Discussion of “High-dimensional autocovariance matrices and optimal linear prediction”
  • Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization
  • Grouped Functional Time Series Forecasting: An Application to Age-Specific Mortality Rates
  • A gradient boosting approach to the Kaggle load forecasting competition
  • Bivariate smoothing of mortality surfaces with cohort and period ridges
  • Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models
  • Crude oil price forecasting based on internet concern using an extreme learning machine
  • Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond
  • Associations between outdoor fungal spores and childhood and adolescent asthma hospitalizations
  • A note on upper bounds for forecast-value-Added relative to naïve forecasts
  • Exploring the influence of short-term temperature patterns on temperature-related mortality: a case-study of Melbourne, Australia
  • Efficient identification of the Pareto optimal set
  • Dynamic algorithm selection for pareto optimal set approximation
  • A note on the validity of cross-validation for evaluating autoregressive time series prediction
  • Exploring the sources of uncertainty: Why does bagging for time series forecasting work?
  • Forecasting with temporal hierarchies
  • Visualising forecasting algorithm performance using time series instance spaces
  • Short-term load forecasting based on a semi-parametric additive model
  • A robust approach for phenological change detection within satellite image time series
  • Modern Strategies for Time Series Regression
  • Anomaly Detection in High-Dimensional Data
  • Forecasting the old‐age dependency ratio to determine a sustainable pension age
  • Hierarchical forecast reconciliation with machine learning
  • Fast Forecast Reconciliation Using Linear Models
  • Visualizing Probability Distributions Across Bivariate Cyclic Temporal Granularities
  • Seasonal functional autoregressive models
  • Dimension Reduction for Outlier Detection Using DOBIN
  • Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters
  • Leave-One-Out Kernel Density Estimates for Outlier Detection
  • Lee-Carter mortality forecasting: A multi-country comparison of variants and extensions
  • Giving a useR! Talk
  • A change of editors
  • Exponential smoothing and non-negative data
  • Encouraging replication and reproducible research
  • Changing of the guard
  • Hierarchical forecasts for Australian domestic tourism
  • The price elasticity of electricity demand in South Australia
  • Stochastic population forecasts using functional data models for mortality, fertility and migration
  • The admissible parameter space for exponential smoothing models
  • Modelling and forecasting Australian domestic tourism
  • The tourism forecasting competition
  • Half-life estimation based on the bias-corrected bootstrap: A highest density region approach
  • Monitoring processes with changing variances
  • Improved interval estimation of long run response from a dynamic linear model: A highest density region approach
  • Measurement of changes in antihypertensive drug utilisation following primary care educational interventions
  • A note on the categorization of demand patterns
  • A Bayesian approach to bandwidth selection for multivariate kernel density estimation
  • A multivariate innovations state space Beveridge-Nelson decomposition
  • 25 years of time series forecasting
  • Density forecasting for long-term peak electricity demand
  • Detecting trend and seasonal changes in satellite image time series
  • Forecasting age-related changes in breast cancer mortality among white and black US women: A functional data approach
  • Forecasting age-specific breast cancer mortality using functional data models
  • Forecasting functional time series
  • Nonparametric time series forecasting with dynamic updating
  • Investigating the influence of synoptic-scale meteorology on air quality using self-organizing maps and generalized additive modelling
  • Method for optimizing coating properties based on an evolutionary algorithm approach
  • Optimal combination forecasts for hierarchical time series
  • Phenological change detection while accounting for abrupt and gradual trends in satellite image time series
  • Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods
  • Rainbow plots, bagplots, and boxplots for functional data
  • Quantifying the influence of local meteorology on air quality using generalized additive models
  • Rejoinder: Forecasting functional time series
  • Rule induction for forecasting method selection: Meta-learning the characteristics of univariate time series
  • The value of feedback in forecasting competitions
  • Using functional data analysis models to estimate future time trends in age-specific breast cancer mortality for the United States and England-Wales
  • Nonparametric time series forecasting with dynamic updating
  • Automatic time series forecasting: The forecast package for R
  • Another look at measures of forecast accuracy
  • Characteristic-based clustering for time series data
  • Forecasting time series with multiple seasonal patterns
  • Do levels of airborne grass pollen influence asthma hospital admissions?
  • Generation of synthetic sequences of half-hourly temperature
  • Tourism forecasting: An introduction
  • The vector innovations structural time series framework: A simple approach to multivariate forecasting
  • Robust forecasting of mortality and fertility rates: A functional data approach
  • Forecast short-term electricity demand using semi-parametric additive model
  • Functionalization of microarray devices: Process optimization using a multiobjective PSO and multiresponse MARS modeling
  • Short-term load forecasting using semi-parametric additive models
  • On continuous-time threshold autoregression
  • Non-Gaussian conditional linear AR(1) models
  • Approximations and Boundary Conditions for Continuous-Time Threshold Autoregressive Processes
  • Computing and Graphing Highest Density Regions
  • Computing and Graphing Highest Density Regions
  • Smoothing non-Gaussian time series with autoregressive structure
  • Sample Quantiles in Statistical Packages
  • 25 Years of IIF Time Series Forecasting: A Selective Review
  • Cycles and synchrony in the Collared Lemming ( Dicrostonyx groenlandicus ) in Arctic North America
  • The interaction between trend and seasonality
  • Using R to teach econometrics
  • Nonparametric Estimation and Symmetry Tests for Conditional Density Functions
  • Sample Quantiles in Statistical Packages
  • Twenty-five years of forecasting
  • Exponential smoothing models: Means and variances for lead-time demand
  • Measuring change in prescription drug utilization in Australia
  • Nonparametric confidence intervals for receiver operating characteristic curves
  • Empirical information criteria for time series forecasting model selection
  • Editorial
  • Prediction intervals for exponential smoothing using two new classes of state space models
  • Improved methods for bandwidth selection when estimating ROC curves
  • Mixed model-based hazard estimation
  • Normative data for the Rosner Test of Visual Analysis Skills on an Australian population
  • Unmasking the Theta method
  • Stochastic models underlying Croston's method for intermittent demand forecasting
  • A state space framework for automatic forecasting using exponential smoothing methods
  • Highest‐density forecast regions for nonlinear and non‐normal time series models
  • Mixed model-based hazard estimation
  • YULE‐WALKER ESTIMATES FOR CONTINUOUS‐TIME AUTOREGRESSIVE MODELS
  • Data visualisation for time series in environmental epidemiology.
  • Sample Quantiles in Statistical Packages
  • Generalized additive modelling of mixed distribution Markov models with application to Melbourne's rainfall
  • Local linear forecasts using cubic smoothing splines
  • Residual diagnostic plots for checking for model mis-specification in time series regression
  • Some properties and generalizations of non-negative bayesian time series models
  • Sensitivity of the estimated air pollution-respiratory admissions relationship to statistical model choice
  • Bandwidth selection for kernel conditional density estimation
  • Dimension reduction for clustering time series using global characteristics
  • Estimating and Visualizing Conditional Densities
  • Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation
  • Forecasting COVID-19 activity in Australia to support pandemic response: May to October 2020
  • Probabilistic forecast reconciliation: Properties, evaluation and score optimisation

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Co-workers & collaborators

Nick Golding

Nick Golding

JAMES MCCAW

JAMES MCCAW

JODIE MCVERNON

JODIE MCVERNON

Rob Moss

Melbourne

Rob Moss

Rob Hyndman's public data