| Working Paper | File Downloads | Abstract Views | 
        
          | Last month | 3 months | 12 months | Total | Last month | 3 months | 12 months | Total | 
          
            | 25 Years of IIF Time Series Forecasting: A Selective Review | 0 | 0 | 1 | 134 | 0 | 3 | 8 | 607 | 
          
            | 25 Years of IIF Time Series Forecasting: A Selective Review | 0 | 1 | 3 | 412 | 2 | 4 | 8 | 955 | 
          
            | A Brief History of Forecasting Competitions | 0 | 0 | 2 | 85 | 0 | 1 | 7 | 121 | 
          
            | A Feature-Based Framework for Detecting Technical Outliers in Water-Quality Data from In Situ Sensors | 0 | 0 | 0 | 26 | 0 | 0 | 1 | 47 | 
          
            | A New Tidy Data Structure to Support Exploration and Modeling of Temporal Data | 0 | 0 | 0 | 37 | 0 | 0 | 2 | 52 | 
          
            | A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction | 2 | 4 | 5 | 740 | 3 | 7 | 12 | 1,890 | 
          
            | A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods | 2 | 2 | 5 | 615 | 2 | 2 | 10 | 1,732 | 
          
            | A comparison of ten principal component methods for forecasting mortality rates | 0 | 1 | 1 | 138 | 1 | 3 | 5 | 329 | 
          
            | A state space model for exponential smoothing with group seasonality | 0 | 1 | 1 | 206 | 0 | 2 | 3 | 525 | 
          
            | An Improved Method for Bandwidth Selection when Estimating ROC Curves | 0 | 0 | 0 | 138 | 1 | 1 | 3 | 557 | 
          
            | Anomaly Detection in High Dimensional Data | 0 | 0 | 0 | 26 | 0 | 1 | 3 | 82 | 
          
            | Anomaly detection in streaming nonstationary temporal data | 0 | 0 | 0 | 122 | 0 | 0 | 2 | 289 | 
          
            | Another Look at Measures of Forecast Accuracy | 1 | 5 | 9 | 1,522 | 5 | 16 | 39 | 3,923 | 
          
            | Automatic time series forecasting: the forecast package for R | 1 | 1 | 3 | 1,601 | 3 | 4 | 16 | 4,708 | 
          
            | Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation | 0 | 0 | 1 | 58 | 0 | 2 | 8 | 204 | 
          
            | Bandwidth Selection for Kernel Conditional Density Estimation | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 1,531 | 
          
            | Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC | 0 | 0 | 2 | 1,028 | 1 | 3 | 8 | 3,615 | 
          
            | Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC | 0 | 0 | 1 | 597 | 1 | 1 | 5 | 2,124 | 
          
            | Bayesian Rank Selection in Multivariate Regression | 0 | 0 | 0 | 51 | 0 | 1 | 2 | 94 | 
          
            | Boosting multi-step autoregressive forecasts | 0 | 0 | 1 | 78 | 0 | 0 | 4 | 129 | 
          
            | Calendar-based Graphics for Visualizing People's Daily Schedules | 0 | 0 | 0 | 4 | 0 | 0 | 4 | 41 | 
          
            | Coherent Mortality Forecasting The Product-ratio Method with Functional Time Series Models | 0 | 1 | 2 | 55 | 0 | 2 | 5 | 304 | 
          
            | Coherent Probabilistic Forecasts for Hierarchical Time Series | 0 | 0 | 1 | 85 | 1 | 1 | 3 | 190 | 
          
            | Coherent mortality forecasting: the product-ratio method with functional time series models | 0 | 0 | 0 | 67 | 0 | 1 | 4 | 189 | 
          
            | Conditional Normalization in Time Series Analysis | 0 | 2 | 3 | 24 | 0 | 4 | 6 | 25 | 
          
            | Cross-temporal Probabilistic Forecast Reconciliation | 0 | 0 | 0 | 23 | 0 | 0 | 1 | 14 | 
          
            | Density forecasting for long-term peak electricity demand | 0 | 0 | 1 | 226 | 0 | 1 | 3 | 597 | 
          
            | Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis | 0 | 0 | 0 | 27 | 1 | 1 | 2 | 23 | 
          
            | Dimension Reduction For Outlier Detection Using DOBIN | 0 | 0 | 1 | 19 | 0 | 0 | 2 | 44 | 
          
            | Distributed ARIMA Models for Ultra-long Time Series | 0 | 0 | 0 | 115 | 0 | 1 | 6 | 184 | 
          
            | Efficient Identification of the Pareto Optimal Set | 0 | 0 | 0 | 13 | 0 | 0 | 2 | 93 | 
          
            | Efficient generation of time series with diverse and controllable characteristics | 0 | 1 | 2 | 69 | 0 | 2 | 5 | 201 | 
          
            | Empirical Information Criteria for Time Series Forecasting Model Selection | 0 | 0 | 1 | 1,000 | 0 | 0 | 2 | 3,395 | 
          
            | Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand | 0 | 0 | 1 | 769 | 1 | 3 | 6 | 2,849 | 
          
            | Exponential smoothing and non-negative data | 0 | 0 | 0 | 85 | 0 | 1 | 4 | 297 | 
          
            | FFORMA: Feature-based forecast model averaging | 1 | 1 | 4 | 128 | 1 | 5 | 16 | 557 | 
          
            | Fast Forecast Reconciliation Using Linear Models | 0 | 0 | 1 | 83 | 0 | 0 | 2 | 187 | 
          
            | Fast computation of reconciled forecasts for hierarchical and grouped time series | 0 | 0 | 0 | 63 | 0 | 0 | 6 | 138 | 
          
            | Forecast Linear AugmentedProjection (FLAP): A Free Lunch to Reduce Forecast Error Variance | 0 | 0 | 20 | 20 | 0 | 1 | 12 | 12 | 
          
            | Forecast Reconciliation: A Review | 0 | 0 | 1 | 23 | 1 | 3 | 9 | 35 | 
          
            | Forecast Reconciliation: A geometric View with New Insights on Bias Correction | 0 | 0 | 1 | 29 | 0 | 0 | 3 | 35 | 
          
            | Forecast Reconciliation: A geometric View with New Insights on Bias Correction | 0 | 0 | 0 | 20 | 0 | 0 | 2 | 51 | 
          
            | Forecasting Swiss Exports Using Bayesian Forecast Reconciliation | 0 | 0 | 0 | 45 | 0 | 0 | 3 | 52 | 
          
            | Forecasting Swiss Exports using Bayesian Forecast Reconciliation | 0 | 0 | 0 | 25 | 0 | 1 | 1 | 34 | 
          
            | Forecasting Time-Series with Correlated Seasonality | 0 | 0 | 0 | 262 | 0 | 0 | 2 | 769 | 
          
            | Forecasting age-related changes in breast cancer mortality among white and black US women: A functional approach | 0 | 0 | 0 | 36 | 0 | 0 | 2 | 211 | 
          
            | Forecasting age-specific breast cancer mortality using functional data models | 0 | 0 | 0 | 164 | 0 | 0 | 1 | 985 | 
          
            | Forecasting for Social Good | 0 | 0 | 0 | 24 | 0 | 1 | 3 | 139 | 
          
            | Forecasting hierarchical and grouped time series through trace minimization | 0 | 0 | 2 | 89 | 2 | 4 | 11 | 196 | 
          
            | Forecasting the Old-Age Dependency Ratio to Determine a Sustainable Pension Age | 1 | 1 | 2 | 28 | 1 | 1 | 5 | 278 | 
          
            | Forecasting time series with complex seasonal patterns using exponential smoothing | 0 | 0 | 3 | 221 | 1 | 1 | 13 | 572 | 
          
            | Forecasting with Temporal Hierarchies | 0 | 0 | 2 | 74 | 0 | 1 | 9 | 247 | 
          
            | Forecasting with Temporal Hierarchies | 0 | 0 | 1 | 51 | 0 | 2 | 7 | 147 | 
          
            | Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbourne's Rainfall | 0 | 0 | 0 | 251 | 0 | 0 | 2 | 1,563 | 
          
            | Grouped functional time series forecasting: An application to age-specific mortality rates | 0 | 1 | 2 | 72 | 0 | 1 | 4 | 119 | 
          
            | Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach | 0 | 0 | 0 | 188 | 0 | 0 | 2 | 904 | 
          
            | Hierarchical Forecasting | 0 | 0 | 1 | 106 | 1 | 2 | 8 | 223 | 
          
            | Hierarchical forecasts for Australian domestic tourism | 0 | 0 | 0 | 128 | 1 | 1 | 2 | 384 | 
          
            | Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach | 0 | 0 | 0 | 13 | 0 | 0 | 2 | 115 | 
          
            | Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach | 0 | 0 | 0 | 3 | 1 | 1 | 8 | 104 | 
          
            | Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering | 0 | 0 | 2 | 26 | 0 | 1 | 7 | 30 | 
          
            | Invertibility Conditions for Exponential Smoothing Models | 0 | 0 | 0 | 417 | 1 | 1 | 2 | 2,638 | 
          
            | Leave-one-out Kernel Density Estimates for Outlier Detection | 0 | 0 | 2 | 18 | 0 | 1 | 8 | 59 | 
          
            | Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions | 0 | 0 | 1 | 212 | 0 | 1 | 4 | 788 | 
          
            | Local Linear Forecasts Using Cubic Smoothing Splines | 0 | 0 | 2 | 561 | 1 | 2 | 5 | 1,978 | 
          
            | Local Linear Multivariate Regression with Variable Bandwidth in the Presence of Heteroscedasticity | 0 | 0 | 0 | 199 | 0 | 0 | 1 | 726 | 
          
            | Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models | 0 | 1 | 2 | 25 | 0 | 2 | 5 | 63 | 
          
            | Long-term forecasts of age-specific participation rates with functional data models | 0 | 0 | 0 | 37 | 0 | 1 | 3 | 76 | 
          
            | Low-dimensional decomposition, smoothing and forecasting of sparse functional data | 0 | 0 | 0 | 71 | 0 | 0 | 3 | 95 | 
          
            | Macroeconomic forecasting for Australia using a large number of predictors | 0 | 0 | 0 | 175 | 0 | 0 | 4 | 303 | 
          
            | Manifold Learning with Approximate Nearest Neighbors | 0 | 0 | 1 | 37 | 0 | 2 | 6 | 82 | 
          
            | Meta-learning how to forecast time series | 0 | 1 | 6 | 213 | 0 | 4 | 16 | 591 | 
          
            | Mixed Model-Based Hazard Estimation | 0 | 0 | 0 | 133 | 0 | 0 | 2 | 644 | 
          
            | Modelling and forecasting Australian domestic tourism | 0 | 0 | 2 | 380 | 0 | 1 | 7 | 931 | 
          
            | Monitoring Processes with Changing Variances | 0 | 0 | 0 | 60 | 0 | 0 | 2 | 170 | 
          
            | Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves | 0 | 0 | 0 | 234 | 1 | 1 | 2 | 1,210 | 
          
            | Non-linear exponential smoothing and positive data | 0 | 0 | 0 | 118 | 0 | 1 | 3 | 529 | 
          
            | Nonlinear Mixed Effects Models for Time Series Forecasting of Smart Meter Demand | 0 | 0 | 0 | 24 | 0 | 0 | 1 | 41 | 
          
            | Nonparametric Estimation and Symmetry Tests for Conditional Density Functions | 0 | 0 | 0 | 183 | 0 | 0 | 2 | 1,026 | 
          
            | Nonparametric autocovariance function estimation | 0 | 0 | 0 | 69 | 0 | 0 | 2 | 1,086 | 
          
            | Nonparametric estimation and symmetry tests for conditional density functions | 0 | 0 | 0 | 4 | 0 | 0 | 3 | 63 | 
          
            | Nonparametric time series forecasting with dynamic updating | 0 | 0 | 0 | 160 | 0 | 1 | 2 | 391 | 
          
            | On normalization and algorithm selection for unsupervised outlier detection | 0 | 0 | 0 | 36 | 0 | 0 | 4 | 87 | 
          
            | Online Conformal Inference for Multi-Step Time Series Forecasting | 0 | 1 | 55 | 55 | 1 | 5 | 92 | 92 | 
          
            | Optimal Forecast Reconciliation with Time Series Selection | 1 | 1 | 23 | 23 | 2 | 2 | 16 | 16 | 
          
            | Optimal Non-negative Forecast Reconciliation | 0 | 1 | 1 | 37 | 1 | 3 | 7 | 95 | 
          
            | Optimal combination forecasts for hierarchical time series | 0 | 1 | 1 | 286 | 0 | 4 | 11 | 683 | 
          
            | Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization | 2 | 3 | 7 | 65 | 3 | 8 | 28 | 153 | 
          
            | Prediction Intervals for Exponential Smoothing State Space Models | 0 | 0 | 2 | 638 | 1 | 2 | 7 | 2,146 | 
          
            | Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality | 0 | 0 | 0 | 52 | 0 | 0 | 5 | 43 | 
          
            | Probabilisitic forecasts in hierarchical time series | 0 | 0 | 0 | 61 | 0 | 0 | 4 | 133 | 
          
            | Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation | 0 | 0 | 0 | 53 | 0 | 1 | 7 | 108 | 
          
            | Probabilistic time series forecasting with boosted additive models: an application to smart meter data | 0 | 0 | 0 | 78 | 0 | 0 | 5 | 176 | 
          
            | Rainbow plots, Bagplots and Boxplots for Functional Data | 0 | 0 | 2 | 86 | 1 | 1 | 5 | 363 | 
          
            | Rating Forecasts for Television Programs | 0 | 0 | 0 | 223 | 1 | 1 | 4 | 640 | 
          
            | Recursive and direct multi-step forecasting: the best of both worlds | 1 | 6 | 30 | 454 | 3 | 23 | 124 | 1,352 | 
          
            | Residual Diagnostic Plots for Checking for model Mis-Specification in Time Series Regression | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,724 | 
          
            | Robust forecasting of mortality and fertility rates: a functional data approach | 0 | 0 | 1 | 429 | 0 | 2 | 9 | 1,231 | 
          
            | STR: A Seasonal-Trend Decomposition Procedure Based on Regression | 0 | 1 | 3 | 155 | 1 | 8 | 18 | 448 | 
          
            | Seasonal Functional Autoregressive Models | 0 | 0 | 1 | 42 | 1 | 1 | 5 | 72 | 
          
            | Short-term load forecasting based on a semi-parametric additive model | 0 | 1 | 2 | 75 | 0 | 2 | 5 | 227 | 
          
            | Some Nonlinear Exponential Smoothing Models are Unstable | 0 | 0 | 1 | 217 | 0 | 0 | 2 | 1,052 | 
          
            | Sparse Multiple Index Modelsfor High-dimensional Nonparametric Forecasting | 0 | 0 | 41 | 41 | 0 | 0 | 14 | 14 | 
          
            | Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016 | 0 | 0 | 1 | 43 | 0 | 1 | 7 | 134 | 
          
            | Statistical Methodological Issues in Studies of Air Pollution and Respiratory Disease | 0 | 0 | 0 | 209 | 0 | 0 | 1 | 1,049 | 
          
            | Stochastic models underlying Croston's method for intermittent demand forecasting | 0 | 0 | 2 | 2,173 | 0 | 0 | 5 | 6,638 | 
          
            | Stochastic population forecasts using functional data models for mortality, fertility and migration | 0 | 0 | 3 | 265 | 0 | 1 | 7 | 868 | 
          
            | The Australian Macro Database: An Online Resource for Macroeconomic Research in Australia | 0 | 0 | 0 | 20 | 1 | 1 | 5 | 61 | 
          
            | The Australian Macro Database: An online resource for macroeconomic research in Australia | 0 | 0 | 0 | 38 | 1 | 1 | 4 | 83 | 
          
            | The Road to Recovery from COVID-19 for Australian Tourism | 0 | 0 | 2 | 66 | 0 | 1 | 6 | 144 | 
          
            | The price elasticity of electricity demand in South Australia | 0 | 0 | 0 | 186 | 0 | 1 | 4 | 476 | 
          
            | The tourism forecasting competition | 0 | 0 | 1 | 156 | 1 | 3 | 7 | 488 | 
          
            | The value of feedback in forecasting competitions | 0 | 1 | 1 | 60 | 0 | 1 | 2 | 197 | 
          
            | The vector innovation structural time series framework: a simple approach to multivariate forecasting | 0 | 0 | 0 | 180 | 1 | 1 | 4 | 497 | 
          
            | Time Series Forecasting: The Case for the Single Source of Error State Space | 0 | 0 | 0 | 335 | 0 | 0 | 3 | 1,301 | 
          
            | Two-dimensional smoothing of mortality rates | 0 | 0 | 0 | 33 | 0 | 2 | 5 | 102 | 
          
            | Unmasking the Theta Method | 0 | 0 | 2 | 311 | 0 | 1 | 4 | 1,221 | 
          
            | Using R to Teach Econometrics | 0 | 0 | 2 | 2,177 | 0 | 0 | 4 | 4,407 | 
          
            | Visualising forecasting Algorithm Performance using Time Series Instance Spaces | 0 | 1 | 1 | 108 | 0 | 3 | 7 | 143 | 
          
            | Visualizing Probability Distributions across Bivariate Cyclic Temporal Granularities | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 7 | 
          
            | Total Working Papers | 12 | 41 | 290 | 25,163 | 53 | 193 | 877 | 82,208 | 
        
        
        
          | Journal Article | File Downloads | Abstract Views | 
        
          | Last month | 3 months | 12 months | Total | Last month | 3 months | 12 months | Total | 
          
            | 25 years of time series forecasting | 0 | 0 | 4 | 259 | 1 | 4 | 24 | 951 | 
          
            | A Bayesian approach to bandwidth selection for multivariate kernel density estimation | 0 | 0 | 0 | 107 | 0 | 1 | 2 | 321 | 
          
            | A brief history of forecasting competitions | 0 | 0 | 1 | 32 | 0 | 0 | 14 | 139 | 
          
            | A change of editors | 0 | 0 | 0 | 7 | 1 | 1 | 2 | 66 | 
          
            | A gradient boosting approach to the Kaggle load forecasting competition | 0 | 0 | 1 | 55 | 3 | 9 | 16 | 317 | 
          
            | A multivariate innovations state space Beveridge-Nelson decomposition | 0 | 0 | 0 | 33 | 0 | 2 | 4 | 167 | 
          
            | A note on the categorization of demand patterns | 0 | 0 | 0 | 5 | 1 | 1 | 4 | 29 | 
          
            | A note on the validity of cross-validation for evaluating autoregressive time series prediction | 2 | 8 | 25 | 271 | 10 | 34 | 90 | 732 | 
          
            | A note on upper bounds for forecast-value-added relative to naïve forecasts | 0 | 0 | 0 | 2 | 0 | 0 | 3 | 42 | 
          
            | A state space framework for automatic forecasting using exponential smoothing methods | 3 | 5 | 12 | 264 | 6 | 18 | 46 | 908 | 
          
            | Another Look at Forecast Accuracy Metrics for Intermittent Demand | 0 | 2 | 6 | 401 | 3 | 13 | 45 | 1,483 | 
          
            | Another look at measures of forecast accuracy | 3 | 9 | 25 | 451 | 10 | 26 | 82 | 1,585 | 
          
            | Assessing mortality inequality in the U.S.: What can be said about the future? | 0 | 0 | 0 | 3 | 0 | 1 | 4 | 13 | 
          
            | Automatic Time Series Forecasting: The forecast Package for R | 0 | 0 | 3 | 482 | 5 | 10 | 37 | 2,283 | 
          
            | Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation | 0 | 0 | 1 | 46 | 1 | 5 | 12 | 195 | 
          
            | Bandwidth selection for kernel conditional density estimation | 0 | 1 | 7 | 117 | 0 | 6 | 17 | 346 | 
          
            | Call for Papers: Special issue of the International Journal of Forecasting on tourism forecasting | 0 | 0 | 0 | 28 | 0 | 0 | 1 | 237 | 
          
            | Changing of the guard | 0 | 0 | 0 | 3 | 0 | 0 | 1 | 41 | 
          
            | Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models | 0 | 0 | 0 | 20 | 0 | 0 | 3 | 137 | 
          
            | Comments on: Exploratory functional data analysis | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 
          
            | Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 2 | 
          
            | Crude oil price forecasting based on internet concern using an extreme learning machine | 0 | 0 | 0 | 22 | 2 | 5 | 10 | 95 | 
          
            | Distributed ARIMA models for ultra-long time series | 2 | 2 | 2 | 6 | 3 | 5 | 9 | 24 | 
          
            | Dynamic algorithm selection for pareto optimal set approximation | 0 | 0 | 0 | 6 | 0 | 0 | 3 | 29 | 
          
            | Early classification of spatio-temporal events using partial information | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 7 | 
          
            | Editorial | 0 | 0 | 0 | 9 | 0 | 0 | 1 | 116 | 
          
            | Encouraging replication and reproducible research | 0 | 0 | 0 | 16 | 1 | 2 | 4 | 82 | 
          
            | Errors on Percentage Errors | 0 | 0 | 0 | 0 | 1 | 3 | 3 | 3 | 
          
            | Exploring the sources of uncertainty: Why does bagging for time series forecasting work? | 0 | 0 | 1 | 21 | 0 | 1 | 8 | 88 | 
          
            | Exponential smoothing models: Means and variances for lead-time demand | 0 | 0 | 0 | 27 | 1 | 2 | 5 | 165 | 
          
            | FFORMA: Feature-based forecast model averaging | 1 | 4 | 9 | 47 | 1 | 9 | 31 | 227 | 
          
            | Fast computation of reconciled forecasts for hierarchical and grouped time series | 0 | 0 | 0 | 6 | 0 | 0 | 4 | 59 | 
          
            | Forecast combinations: An over 50-year review | 0 | 3 | 10 | 28 | 0 | 12 | 31 | 66 | 
          
            | Forecast reconciliation: A geometric view with new insights on bias correction | 1 | 1 | 3 | 12 | 1 | 3 | 13 | 56 | 
          
            | Forecast reconciliation: A review | 0 | 3 | 5 | 8 | 2 | 14 | 32 | 41 | 
          
            | Forecasting Swiss exports using Bayesian forecast reconciliation | 0 | 0 | 0 | 5 | 0 | 1 | 2 | 24 | 
          
            | Forecasting for social good | 0 | 0 | 1 | 3 | 1 | 2 | 6 | 13 | 
          
            | Forecasting in social settings: The state of the art | 1 | 1 | 1 | 16 | 2 | 3 | 11 | 102 | 
          
            | Forecasting interrupted time series | 1 | 1 | 1 | 1 | 1 | 1 | 4 | 4 | 
          
            | Forecasting time series with multiple seasonal patterns | 0 | 0 | 0 | 187 | 1 | 1 | 3 | 664 | 
          
            | Forecasting with temporal hierarchies | 0 | 1 | 7 | 22 | 3 | 11 | 30 | 106 | 
          
            | Forecasting, causality and feedback | 0 | 0 | 2 | 9 | 0 | 0 | 8 | 22 | 
          
            | Free Open-Source Forecasting Using R | 0 | 0 | 2 | 168 | 0 | 1 | 6 | 492 | 
          
            | Half-life estimation based on the bias-corrected bootstrap: A highest density region approach | 0 | 0 | 0 | 41 | 0 | 0 | 3 | 223 | 
          
            | Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data | 0 | 2 | 5 | 9 | 1 | 6 | 12 | 30 | 
          
            | Hierarchical forecasts for Australian domestic tourism | 0 | 1 | 1 | 100 | 0 | 3 | 5 | 400 | 
          
            | Improved interval estimation of long run response from a dynamic linear model: A highest density region approach | 0 | 0 | 0 | 11 | 0 | 0 | 2 | 125 | 
          
            | Improved methods for bandwidth selection when estimating ROC curves | 0 | 0 | 0 | 11 | 0 | 0 | 2 | 83 | 
          
            | Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering | 0 | 1 | 1 | 1 | 0 | 3 | 3 | 3 | 
          
            | Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions | 0 | 0 | 0 | 70 | 0 | 0 | 3 | 458 | 
          
            | LoMEF: A framework to produce local explanations for global model time series forecasts | 0 | 0 | 0 | 1 | 1 | 2 | 6 | 12 | 
          
            | MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns | 0 | 0 | 5 | 5 | 2 | 4 | 17 | 17 | 
          
            | Macroeconomic forecasting for Australia using a large number of predictors | 0 | 1 | 2 | 8 | 1 | 4 | 12 | 47 | 
          
            | Minimum Sample Size requirements for Seasonal Forecasting Models | 1 | 1 | 3 | 217 | 3 | 9 | 31 | 1,103 | 
          
            | Modern Strategies for Time Series Regression | 0 | 0 | 1 | 1 | 0 | 1 | 3 | 12 | 
          
            | Monitoring processes with changing variances | 0 | 0 | 0 | 20 | 0 | 2 | 3 | 123 | 
          
            | Nonparametric time series forecasting with dynamic updating | 0 | 0 | 0 | 3 | 0 | 1 | 2 | 56 | 
          
            | Non‐linear mixed‐effects models for time series forecasting of smart meter demand | 0 | 1 | 1 | 4 | 0 | 1 | 4 | 14 | 
          
            | On continuous-time threshold autoregression | 0 | 0 | 0 | 51 | 0 | 1 | 3 | 176 | 
          
            | Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization | 5 | 9 | 14 | 30 | 9 | 17 | 36 | 111 | 
          
            | Optimal combination forecasts for hierarchical time series | 0 | 0 | 3 | 86 | 5 | 9 | 22 | 380 | 
          
            | Optimal forecast reconciliation with time series selection | 1 | 1 | 1 | 1 | 2 | 3 | 3 | 3 | 
          
            | Optimally Reconciling Forecasts in a Hierarchy | 0 | 0 | 2 | 172 | 0 | 0 | 9 | 432 | 
          
            | Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods | 0 | 0 | 0 | 20 | 0 | 0 | 1 | 136 | 
          
            | Predicting sediment and nutrient concentrations from high-frequency water-quality data | 0 | 0 | 0 | 0 | 0 | 1 | 3 | 7 | 
          
            | Prediction intervals for exponential smoothing using two new classes of state space models | 0 | 0 | 1 | 150 | 0 | 0 | 8 | 581 | 
          
            | Principles and algorithms for forecasting groups of time series: Locality and globality | 3 | 3 | 3 | 9 | 14 | 16 | 25 | 68 | 
          
            | Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond | 0 | 0 | 20 | 151 | 3 | 10 | 51 | 569 | 
          
            | Probabilistic forecast reconciliation: Properties, evaluation and score optimisation | 0 | 0 | 5 | 9 | 0 | 0 | 15 | 28 | 
          
            | Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 2 | 
          
            | Robust forecasting of mortality and fertility rates: A functional data approach | 1 | 2 | 14 | 371 | 2 | 6 | 36 | 1,001 | 
          
            | STR: Seasonal-Trend Decomposition Using Regression | 0 | 0 | 3 | 11 | 1 | 3 | 17 | 67 | 
          
            | Seasonal functional autoregressive models | 0 | 0 | 1 | 5 | 0 | 0 | 12 | 29 | 
          
            | Smoothing non-Gaussian time series with autoregressive structure | 0 | 0 | 0 | 29 | 0 | 0 | 1 | 182 | 
          
            | Some Properties and Generalizations of Non‐negative Bayesian Time Series Models | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 8 | 
          
            | Stochastic models underlying Croston's method for intermittent demand forecasting | 1 | 1 | 4 | 505 | 2 | 3 | 10 | 1,884 | 
          
            | Stochastic population forecasts using functional data models for mortality, fertility and migration | 0 | 2 | 7 | 145 | 1 | 5 | 18 | 410 | 
          
            | The admissible parameter space for exponential smoothing models | 0 | 0 | 0 | 89 | 0 | 0 | 3 | 244 | 
          
            | The interaction between trend and seasonality | 0 | 0 | 0 | 84 | 0 | 0 | 43 | 335 | 
          
            | The price elasticity of electricity demand in South Australia | 0 | 2 | 6 | 120 | 1 | 4 | 14 | 434 | 
          
            | The tourism forecasting competition | 0 | 1 | 2 | 27 | 0 | 1 | 10 | 192 | 
          
            | The tourism forecasting competition | 0 | 1 | 1 | 55 | 1 | 2 | 10 | 424 | 
          
            | The value of feedback in forecasting competitions | 0 | 0 | 0 | 12 | 1 | 2 | 4 | 133 | 
          
            | The value of feedback in forecasting competitions | 0 | 0 | 0 | 5 | 1 | 1 | 2 | 76 | 
          
            | Tourism forecasting: An introduction | 0 | 0 | 0 | 49 | 1 | 1 | 3 | 154 | 
          
            | Twenty-five years of forecasting | 0 | 0 | 0 | 64 | 1 | 1 | 2 | 182 | 
          
            | Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 
          
            | Unmasking the Theta method | 0 | 0 | 4 | 81 | 0 | 3 | 11 | 423 | 
          
            | Using R to teach econometrics | 0 | 0 | 2 | 1,489 | 1 | 3 | 8 | 3,480 | 
          
            | Visualising forecasting algorithm performance using time series instance spaces | 0 | 0 | 2 | 31 | 0 | 2 | 8 | 150 | 
          
            | YULE‐WALKER ESTIMATES FOR CONTINUOUS‐TIME AUTOREGRESSIVE MODELS | 0 | 0 | 1 | 6 | 0 | 0 | 3 | 18 | 
          
            | Total Journal Articles | 26 | 70 | 245 | 7,565 | 116 | 339 | 1,136 | 27,505 |