| 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 |
2 |
2 |
10 |
609 |
| 25 Years of IIF Time Series Forecasting: A Selective Review |
0 |
0 |
3 |
412 |
1 |
4 |
9 |
957 |
| A Brief History of Forecasting Competitions |
0 |
0 |
1 |
85 |
2 |
4 |
10 |
125 |
| 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 |
1 |
1 |
3 |
53 |
| A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction |
1 |
3 |
6 |
741 |
3 |
9 |
18 |
1,896 |
| A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods |
0 |
2 |
5 |
615 |
3 |
6 |
12 |
1,736 |
| A comparison of ten principal component methods for forecasting mortality rates |
0 |
0 |
1 |
138 |
3 |
6 |
10 |
334 |
| A state space model for exponential smoothing with group seasonality |
0 |
0 |
1 |
206 |
1 |
2 |
4 |
527 |
| An Improved Method for Bandwidth Selection when Estimating ROC Curves |
0 |
0 |
0 |
138 |
0 |
1 |
3 |
557 |
| Anomaly Detection in High Dimensional Data |
0 |
0 |
0 |
26 |
1 |
1 |
4 |
83 |
| Anomaly detection in streaming nonstationary temporal data |
0 |
0 |
0 |
122 |
0 |
0 |
2 |
289 |
| Another Look at Measures of Forecast Accuracy |
1 |
4 |
12 |
1,525 |
8 |
35 |
64 |
3,953 |
| Automatic time series forecasting: the forecast package for R |
1 |
2 |
3 |
1,602 |
9 |
16 |
27 |
4,721 |
| Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation |
0 |
0 |
1 |
58 |
3 |
6 |
12 |
210 |
| Bandwidth Selection for Kernel Conditional Density Estimation |
0 |
0 |
0 |
0 |
0 |
0 |
3 |
1,531 |
| Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC |
0 |
0 |
1 |
597 |
0 |
2 |
5 |
2,125 |
| Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC |
0 |
0 |
1 |
1,028 |
1 |
4 |
9 |
3,618 |
| Bayesian Rank Selection in Multivariate Regression |
0 |
0 |
0 |
51 |
1 |
6 |
8 |
100 |
| Boosting multi-step autoregressive forecasts |
0 |
0 |
1 |
78 |
1 |
2 |
6 |
131 |
| Calendar-based Graphics for Visualizing People's Daily Schedules |
0 |
0 |
0 |
4 |
0 |
0 |
2 |
41 |
| Coherent Mortality Forecasting The Product-ratio Method with Functional Time Series Models |
0 |
0 |
2 |
55 |
0 |
1 |
6 |
305 |
| Coherent Probabilistic Forecasts for Hierarchical Time Series |
0 |
0 |
0 |
85 |
3 |
4 |
5 |
193 |
| Coherent mortality forecasting: the product-ratio method with functional time series models |
0 |
0 |
0 |
67 |
2 |
2 |
6 |
191 |
| Conditional Normalization in Time Series Analysis |
0 |
0 |
3 |
24 |
3 |
3 |
9 |
28 |
| Cross-temporal Probabilistic Forecast Reconciliation |
0 |
0 |
0 |
23 |
0 |
2 |
2 |
16 |
| Density forecasting for long-term peak electricity demand |
0 |
0 |
1 |
226 |
2 |
3 |
6 |
600 |
| Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis |
0 |
0 |
0 |
27 |
0 |
2 |
3 |
24 |
| Dimension Reduction For Outlier Detection Using DOBIN |
0 |
0 |
0 |
19 |
1 |
2 |
3 |
46 |
| Distributed ARIMA Models for Ultra-long Time Series |
0 |
0 |
0 |
115 |
1 |
4 |
10 |
188 |
| Efficient Identification of the Pareto Optimal Set |
0 |
0 |
0 |
13 |
0 |
1 |
3 |
94 |
| Efficient generation of time series with diverse and controllable characteristics |
0 |
0 |
2 |
69 |
1 |
1 |
6 |
202 |
| Empirical Information Criteria for Time Series Forecasting Model Selection |
0 |
0 |
0 |
1,000 |
1 |
1 |
2 |
3,396 |
| Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand |
0 |
0 |
1 |
769 |
0 |
1 |
5 |
2,849 |
| Exponential smoothing and non-negative data |
0 |
0 |
0 |
85 |
1 |
2 |
5 |
299 |
| FFORMA: Feature-based forecast model averaging |
0 |
1 |
4 |
128 |
1 |
3 |
18 |
559 |
| Fast Forecast Reconciliation Using Linear Models |
0 |
0 |
0 |
83 |
1 |
1 |
2 |
188 |
| Fast computation of reconciled forecasts for hierarchical and grouped time series |
0 |
0 |
0 |
63 |
2 |
3 |
9 |
141 |
| Forecast Linear AugmentedProjection (FLAP): A Free Lunch to Reduce Forecast Error Variance |
0 |
0 |
20 |
20 |
1 |
2 |
14 |
14 |
| Forecast Reconciliation: A Review |
0 |
1 |
2 |
24 |
2 |
6 |
13 |
40 |
| Forecast Reconciliation: A geometric View with New Insights on Bias Correction |
0 |
0 |
0 |
20 |
1 |
1 |
3 |
52 |
| Forecast Reconciliation: A geometric View with New Insights on Bias Correction |
0 |
0 |
1 |
29 |
0 |
2 |
5 |
37 |
| Forecasting Swiss Exports Using Bayesian Forecast Reconciliation |
0 |
0 |
0 |
45 |
4 |
4 |
6 |
56 |
| Forecasting Swiss Exports using Bayesian Forecast Reconciliation |
0 |
0 |
0 |
25 |
4 |
5 |
6 |
39 |
| Forecasting Time-Series with Correlated Seasonality |
0 |
0 |
0 |
262 |
0 |
2 |
3 |
771 |
| 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 |
2 |
3 |
4 |
988 |
| Forecasting for Social Good |
0 |
0 |
0 |
24 |
1 |
1 |
4 |
140 |
| Forecasting hierarchical and grouped time series through trace minimization |
1 |
1 |
2 |
90 |
1 |
5 |
11 |
199 |
| Forecasting the Old-Age Dependency Ratio to Determine a Sustainable Pension Age |
0 |
1 |
1 |
28 |
2 |
4 |
7 |
281 |
| Forecasting time series with complex seasonal patterns using exponential smoothing |
0 |
0 |
3 |
221 |
6 |
13 |
23 |
584 |
| Forecasting with Temporal Hierarchies |
0 |
0 |
0 |
51 |
2 |
5 |
10 |
152 |
| Forecasting with Temporal Hierarchies |
0 |
0 |
0 |
74 |
1 |
4 |
10 |
251 |
| 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 |
0 |
2 |
72 |
0 |
0 |
4 |
119 |
| Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach |
0 |
0 |
0 |
188 |
3 |
3 |
5 |
907 |
| Hierarchical Forecasting |
0 |
0 |
0 |
106 |
5 |
8 |
14 |
230 |
| Hierarchical forecasts for Australian domestic tourism |
0 |
0 |
0 |
128 |
2 |
4 |
5 |
387 |
| 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 |
0 |
3 |
10 |
106 |
| Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering |
1 |
1 |
3 |
27 |
6 |
6 |
11 |
36 |
| Invertibility Conditions for Exponential Smoothing Models |
1 |
1 |
1 |
418 |
1 |
3 |
4 |
2,640 |
| Leave-one-out Kernel Density Estimates for Outlier Detection |
0 |
0 |
2 |
18 |
4 |
7 |
14 |
66 |
| Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions |
0 |
0 |
0 |
212 |
2 |
2 |
5 |
790 |
| Local Linear Forecasts Using Cubic Smoothing Splines |
0 |
0 |
2 |
561 |
2 |
4 |
8 |
1,981 |
| Local Linear Multivariate Regression with Variable Bandwidth in the Presence of Heteroscedasticity |
0 |
0 |
0 |
199 |
1 |
2 |
3 |
728 |
| Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models |
0 |
0 |
1 |
25 |
1 |
1 |
4 |
64 |
| Long-term forecasts of age-specific participation rates with functional data models |
0 |
0 |
0 |
37 |
1 |
2 |
5 |
78 |
| Low-dimensional decomposition, smoothing and forecasting of sparse functional data |
0 |
0 |
0 |
71 |
1 |
1 |
4 |
96 |
| Macroeconomic forecasting for Australia using a large number of predictors |
0 |
0 |
0 |
175 |
2 |
5 |
9 |
308 |
| Manifold Learning with Approximate Nearest Neighbors |
0 |
0 |
0 |
37 |
2 |
3 |
6 |
85 |
| Meta-learning how to forecast time series |
1 |
1 |
4 |
214 |
2 |
5 |
17 |
596 |
| Mixed Model-Based Hazard Estimation |
0 |
0 |
0 |
133 |
0 |
0 |
2 |
644 |
| Modelling and forecasting Australian domestic tourism |
0 |
0 |
2 |
380 |
1 |
1 |
8 |
932 |
| Monitoring Processes with Changing Variances |
1 |
1 |
1 |
61 |
4 |
5 |
7 |
175 |
| Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves |
0 |
0 |
0 |
234 |
1 |
3 |
4 |
1,212 |
| Non-linear exponential smoothing and positive data |
0 |
0 |
0 |
118 |
0 |
2 |
4 |
531 |
| Nonlinear Mixed Effects Models for Time Series Forecasting of Smart Meter Demand |
0 |
0 |
0 |
24 |
1 |
1 |
2 |
42 |
| Nonparametric Estimation and Symmetry Tests for Conditional Density Functions |
0 |
0 |
0 |
183 |
2 |
2 |
4 |
1,028 |
| Nonparametric autocovariance function estimation |
0 |
0 |
0 |
69 |
1 |
2 |
4 |
1,088 |
| Nonparametric estimation and symmetry tests for conditional density functions |
0 |
0 |
0 |
4 |
1 |
2 |
5 |
65 |
| Nonparametric time series forecasting with dynamic updating |
0 |
0 |
0 |
160 |
1 |
1 |
3 |
392 |
| On normalization and algorithm selection for unsupervised outlier detection |
0 |
0 |
0 |
36 |
2 |
2 |
5 |
89 |
| Online Conformal Inference for Multi-Step Time Series Forecasting |
1 |
1 |
56 |
56 |
3 |
8 |
99 |
99 |
| Optimal Forecast Reconciliation with Time Series Selection |
1 |
2 |
24 |
24 |
1 |
3 |
17 |
17 |
| Optimal Non-negative Forecast Reconciliation |
0 |
0 |
1 |
37 |
5 |
8 |
13 |
102 |
| Optimal combination forecasts for hierarchical time series |
0 |
0 |
1 |
286 |
2 |
5 |
14 |
688 |
| Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization |
0 |
3 |
7 |
66 |
6 |
13 |
33 |
163 |
| Prediction Intervals for Exponential Smoothing State Space Models |
1 |
1 |
3 |
639 |
2 |
5 |
10 |
2,150 |
| Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality |
0 |
0 |
0 |
52 |
1 |
1 |
5 |
44 |
| Probabilisitic forecasts in hierarchical time series |
0 |
0 |
0 |
61 |
2 |
2 |
5 |
135 |
| Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation |
0 |
0 |
0 |
53 |
3 |
7 |
13 |
115 |
| Probabilistic time series forecasting with boosted additive models: an application to smart meter data |
0 |
0 |
0 |
78 |
0 |
0 |
3 |
176 |
| Rainbow plots, Bagplots and Boxplots for Functional Data |
1 |
1 |
3 |
87 |
1 |
4 |
8 |
366 |
| Rating Forecasts for Television Programs |
0 |
0 |
0 |
223 |
2 |
4 |
7 |
643 |
| Recursive and direct multi-step forecasting: the best of both worlds |
3 |
5 |
24 |
458 |
15 |
24 |
105 |
1,373 |
| Residual Diagnostic Plots for Checking for model Mis-Specification in Time Series Regression |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1,725 |
| Robust forecasting of mortality and fertility rates: a functional data approach |
1 |
1 |
1 |
430 |
4 |
4 |
11 |
1,235 |
| STR: A Seasonal-Trend Decomposition Procedure Based on Regression |
0 |
0 |
2 |
155 |
2 |
5 |
19 |
452 |
| Seasonal Functional Autoregressive Models |
0 |
0 |
1 |
42 |
1 |
4 |
8 |
75 |
| Short-term load forecasting based on a semi-parametric additive model |
0 |
0 |
2 |
75 |
2 |
4 |
9 |
231 |
| Some Nonlinear Exponential Smoothing Models are Unstable |
0 |
0 |
0 |
217 |
2 |
3 |
4 |
1,055 |
| Sparse Multiple Index Modelsfor High-dimensional Nonparametric Forecasting |
1 |
1 |
42 |
42 |
2 |
3 |
17 |
17 |
| Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016 |
0 |
0 |
1 |
43 |
0 |
1 |
8 |
135 |
| 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 |
1 |
2 |
7 |
6,640 |
| Stochastic population forecasts using functional data models for mortality, fertility and migration |
1 |
1 |
4 |
266 |
4 |
4 |
11 |
872 |
| The Australian Macro Database: An Online Resource for Macroeconomic Research in Australia |
0 |
0 |
0 |
20 |
1 |
2 |
4 |
62 |
| The Australian Macro Database: An online resource for macroeconomic research in Australia |
0 |
0 |
0 |
38 |
0 |
1 |
3 |
83 |
| The Road to Recovery from COVID-19 for Australian Tourism |
1 |
1 |
3 |
67 |
2 |
5 |
10 |
149 |
| The price elasticity of electricity demand in South Australia |
1 |
1 |
1 |
187 |
2 |
3 |
6 |
479 |
| The tourism forecasting competition |
0 |
0 |
1 |
156 |
5 |
8 |
14 |
495 |
| The value of feedback in forecasting competitions |
0 |
0 |
1 |
60 |
6 |
6 |
8 |
203 |
| The vector innovation structural time series framework: a simple approach to multivariate forecasting |
0 |
0 |
0 |
180 |
0 |
1 |
4 |
497 |
| Time Series Forecasting: The Case for the Single Source of Error State Space |
0 |
0 |
0 |
335 |
0 |
0 |
2 |
1,301 |
| Two-dimensional smoothing of mortality rates |
0 |
0 |
0 |
33 |
1 |
2 |
7 |
104 |
| Unmasking the Theta Method |
0 |
0 |
2 |
311 |
3 |
8 |
12 |
1,229 |
| Using R to Teach Econometrics |
0 |
0 |
2 |
2,177 |
1 |
1 |
5 |
4,408 |
| Visualising forecasting Algorithm Performance using Time Series Instance Spaces |
0 |
0 |
1 |
108 |
3 |
3 |
9 |
146 |
| Visualizing Probability Distributions across Bivariate Cyclic Temporal Granularities |
0 |
0 |
0 |
0 |
0 |
1 |
2 |
8 |
| Total Working Papers |
20 |
37 |
282 |
25,188 |
221 |
436 |
1,137 |
82,591 |
| 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 |
3 |
259 |
4 |
11 |
27 |
961 |
| A Bayesian approach to bandwidth selection for multivariate kernel density estimation |
0 |
0 |
0 |
107 |
1 |
1 |
3 |
322 |
| A brief history of forecasting competitions |
0 |
0 |
1 |
32 |
2 |
2 |
14 |
141 |
| A change of editors |
0 |
0 |
0 |
7 |
1 |
2 |
3 |
67 |
| A gradient boosting approach to the Kaggle load forecasting competition |
0 |
0 |
1 |
55 |
2 |
7 |
19 |
321 |
| A multivariate innovations state space Beveridge-Nelson decomposition |
0 |
0 |
0 |
33 |
0 |
0 |
4 |
167 |
| A note on the categorization of demand patterns |
0 |
0 |
0 |
5 |
1 |
4 |
7 |
32 |
| A note on the validity of cross-validation for evaluating autoregressive time series prediction |
2 |
5 |
23 |
274 |
11 |
28 |
90 |
750 |
| A note on upper bounds for forecast-value-added relative to naïve forecasts |
0 |
0 |
0 |
2 |
0 |
0 |
2 |
42 |
| A state space framework for automatic forecasting using exponential smoothing methods |
0 |
7 |
14 |
268 |
9 |
25 |
58 |
927 |
| Another Look at Forecast Accuracy Metrics for Intermittent Demand |
0 |
0 |
6 |
401 |
2 |
6 |
42 |
1,486 |
| Another look at measures of forecast accuracy |
4 |
8 |
27 |
456 |
20 |
47 |
101 |
1,622 |
| Assessing mortality inequality in the U.S.: What can be said about the future? |
0 |
0 |
0 |
3 |
3 |
3 |
7 |
16 |
| Automatic Time Series Forecasting: The forecast Package for R |
0 |
0 |
2 |
482 |
2 |
14 |
39 |
2,292 |
| Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation |
1 |
1 |
2 |
47 |
4 |
14 |
23 |
208 |
| Bandwidth selection for kernel conditional density estimation |
1 |
2 |
8 |
119 |
4 |
10 |
26 |
356 |
| Call for Papers: Special issue of the International Journal of Forecasting on tourism forecasting |
0 |
0 |
0 |
28 |
0 |
1 |
2 |
238 |
| Changing of the guard |
0 |
0 |
0 |
3 |
0 |
1 |
2 |
42 |
| Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models |
0 |
0 |
0 |
20 |
2 |
2 |
4 |
139 |
| Comments on: Exploratory functional data analysis |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
1 |
| Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues |
0 |
0 |
0 |
1 |
1 |
3 |
3 |
5 |
| Crude oil price forecasting based on internet concern using an extreme learning machine |
0 |
0 |
0 |
22 |
0 |
2 |
9 |
95 |
| Distributed ARIMA models for ultra-long time series |
0 |
2 |
2 |
6 |
0 |
3 |
8 |
24 |
| Dynamic algorithm selection for pareto optimal set approximation |
0 |
0 |
0 |
6 |
1 |
2 |
5 |
31 |
| Early classification of spatio-temporal events using partial information |
0 |
0 |
0 |
0 |
2 |
2 |
3 |
9 |
| Editorial |
0 |
0 |
0 |
9 |
0 |
0 |
1 |
116 |
| Encouraging replication and reproducible research |
0 |
0 |
0 |
16 |
1 |
2 |
5 |
83 |
| Errors on Percentage Errors |
3 |
3 |
3 |
3 |
3 |
5 |
7 |
7 |
| Exploring the sources of uncertainty: Why does bagging for time series forecasting work? |
1 |
1 |
1 |
22 |
2 |
3 |
8 |
91 |
| Exponential smoothing models: Means and variances for lead-time demand |
0 |
0 |
0 |
27 |
1 |
2 |
6 |
166 |
| FFORMA: Feature-based forecast model averaging |
1 |
3 |
11 |
49 |
4 |
7 |
34 |
233 |
| Fast computation of reconciled forecasts for hierarchical and grouped time series |
0 |
0 |
0 |
6 |
1 |
1 |
5 |
60 |
| Forecast combinations: An over 50-year review |
0 |
4 |
13 |
32 |
9 |
19 |
47 |
85 |
| Forecast reconciliation: A geometric view with new insights on bias correction |
0 |
1 |
2 |
12 |
3 |
4 |
15 |
59 |
| Forecast reconciliation: A review |
0 |
4 |
7 |
12 |
5 |
17 |
42 |
56 |
| Forecasting Swiss exports using Bayesian forecast reconciliation |
0 |
0 |
0 |
5 |
1 |
1 |
3 |
25 |
| Forecasting for social good |
0 |
0 |
1 |
3 |
3 |
6 |
11 |
18 |
| Forecasting in social settings: The state of the art |
2 |
4 |
4 |
19 |
4 |
7 |
16 |
107 |
| Forecasting interrupted time series |
0 |
1 |
1 |
1 |
3 |
5 |
8 |
8 |
| Forecasting time series with multiple seasonal patterns |
0 |
1 |
1 |
188 |
1 |
4 |
6 |
667 |
| Forecasting with temporal hierarchies |
0 |
1 |
8 |
23 |
3 |
12 |
36 |
115 |
| Forecasting, causality and feedback |
0 |
0 |
1 |
9 |
0 |
0 |
6 |
22 |
| Free Open-Source Forecasting Using R |
0 |
0 |
2 |
168 |
1 |
2 |
7 |
494 |
| Half-life estimation based on the bias-corrected bootstrap: A highest density region approach |
0 |
0 |
0 |
41 |
0 |
1 |
4 |
224 |
| Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data |
0 |
0 |
5 |
9 |
3 |
6 |
16 |
35 |
| Hierarchical forecasts for Australian domestic tourism |
1 |
1 |
2 |
101 |
6 |
7 |
12 |
407 |
| Improved interval estimation of long run response from a dynamic linear model: A highest density region approach |
0 |
0 |
0 |
11 |
2 |
5 |
7 |
130 |
| 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 |
0 |
1 |
1 |
2 |
2 |
5 |
5 |
| 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 |
2 |
3 |
6 |
14 |
| MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns |
1 |
2 |
7 |
7 |
5 |
9 |
24 |
24 |
| Macroeconomic forecasting for Australia using a large number of predictors |
0 |
0 |
2 |
8 |
2 |
5 |
16 |
51 |
| Minimum Sample Size requirements for Seasonal Forecasting Models |
1 |
3 |
5 |
219 |
2 |
8 |
30 |
1,108 |
| Modern Strategies for Time Series Regression |
0 |
0 |
1 |
1 |
0 |
1 |
4 |
13 |
| Monitoring processes with changing variances |
0 |
0 |
0 |
20 |
1 |
1 |
4 |
124 |
| Nonparametric time series forecasting with dynamic updating |
0 |
0 |
0 |
3 |
5 |
7 |
9 |
63 |
| Non‐linear mixed‐effects models for time series forecasting of smart meter demand |
1 |
1 |
2 |
5 |
1 |
1 |
5 |
15 |
| On continuous-time threshold autoregression |
0 |
0 |
0 |
51 |
0 |
0 |
3 |
176 |
| Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization |
1 |
8 |
15 |
33 |
6 |
20 |
40 |
122 |
| Optimal combination forecasts for hierarchical time series |
0 |
0 |
2 |
86 |
7 |
15 |
27 |
390 |
| Optimal forecast reconciliation with time series selection |
0 |
1 |
1 |
1 |
2 |
4 |
5 |
5 |
| Optimally Reconciling Forecasts in a Hierarchy |
0 |
0 |
2 |
172 |
3 |
3 |
11 |
435 |
| Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods |
0 |
0 |
0 |
20 |
3 |
4 |
5 |
140 |
| Predicting sediment and nutrient concentrations from high-frequency water-quality data |
0 |
0 |
0 |
0 |
1 |
2 |
5 |
9 |
| Prediction intervals for exponential smoothing using two new classes of state space models |
0 |
1 |
2 |
151 |
2 |
4 |
8 |
585 |
| Principles and algorithms for forecasting groups of time series: Locality and globality |
1 |
5 |
5 |
11 |
6 |
32 |
43 |
86 |
| Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond |
1 |
3 |
20 |
154 |
4 |
12 |
54 |
578 |
| Probabilistic forecast reconciliation: Properties, evaluation and score optimisation |
0 |
0 |
4 |
9 |
3 |
7 |
19 |
35 |
| Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters |
1 |
1 |
1 |
1 |
2 |
2 |
3 |
4 |
| Robust forecasting of mortality and fertility rates: A functional data approach |
0 |
1 |
11 |
371 |
6 |
11 |
38 |
1,010 |
| STR: Seasonal-Trend Decomposition Using Regression |
0 |
0 |
1 |
11 |
2 |
4 |
13 |
70 |
| Seasonal functional autoregressive models |
0 |
0 |
1 |
5 |
0 |
1 |
13 |
30 |
| 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 |
2 |
2 |
4 |
10 |
| Stochastic models underlying Croston's method for intermittent demand forecasting |
1 |
2 |
5 |
506 |
3 |
8 |
16 |
1,890 |
| Stochastic population forecasts using functional data models for mortality, fertility and migration |
1 |
3 |
7 |
148 |
2 |
7 |
16 |
416 |
| The admissible parameter space for exponential smoothing models |
0 |
0 |
0 |
89 |
2 |
2 |
5 |
246 |
| The interaction between trend and seasonality |
0 |
0 |
0 |
84 |
1 |
1 |
44 |
336 |
| The price elasticity of electricity demand in South Australia |
0 |
0 |
5 |
120 |
4 |
5 |
17 |
438 |
| The tourism forecasting competition |
0 |
0 |
1 |
27 |
0 |
0 |
8 |
192 |
| The tourism forecasting competition |
0 |
0 |
1 |
55 |
3 |
7 |
16 |
430 |
| The value of feedback in forecasting competitions |
0 |
0 |
0 |
12 |
3 |
4 |
7 |
136 |
| The value of feedback in forecasting competitions |
0 |
0 |
0 |
5 |
1 |
2 |
3 |
77 |
| Tourism forecasting: An introduction |
0 |
1 |
1 |
50 |
1 |
3 |
5 |
156 |
| Twenty-five years of forecasting |
0 |
0 |
0 |
64 |
1 |
2 |
3 |
183 |
| Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data |
0 |
0 |
0 |
0 |
1 |
2 |
2 |
2 |
| Unmasking the Theta method |
0 |
0 |
2 |
81 |
2 |
3 |
12 |
426 |
| Using R to teach econometrics |
0 |
0 |
1 |
1,489 |
2 |
3 |
8 |
3,482 |
| Visualising forecasting algorithm performance using time series instance spaces |
0 |
0 |
2 |
31 |
1 |
1 |
8 |
151 |
| YULE‐WALKER ESTIMATES FOR CONTINUOUS‐TIME AUTOREGRESSIVE MODELS |
0 |
0 |
1 |
6 |
1 |
2 |
5 |
20 |
| Total Journal Articles |
25 |
81 |
260 |
7,620 |
226 |
519 |
1,379 |
27,908 |
LogEc is hosted by the
Örebro University School of Business.