| 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 |
2 |
412 |
0 |
5 |
12 |
962 |
| 25 Years of IIF Time Series Forecasting: A Selective Review |
0 |
1 |
2 |
135 |
0 |
7 |
13 |
616 |
| A Brief History of Forecasting Competitions |
0 |
1 |
2 |
86 |
0 |
12 |
20 |
137 |
| A Feature-Based Framework for Detecting Technical Outliers in Water-Quality Data from In Situ Sensors |
0 |
0 |
0 |
26 |
1 |
4 |
4 |
51 |
| A New Tidy Data Structure to Support Exploration and Modeling of Temporal Data |
0 |
0 |
0 |
37 |
0 |
5 |
7 |
58 |
| A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction |
0 |
0 |
6 |
741 |
1 |
5 |
20 |
1,901 |
| A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods |
0 |
0 |
4 |
615 |
3 |
11 |
20 |
1,747 |
| A comparison of ten principal component methods for forecasting mortality rates |
1 |
1 |
2 |
139 |
3 |
11 |
19 |
345 |
| A state space model for exponential smoothing with group seasonality |
0 |
1 |
2 |
207 |
7 |
16 |
20 |
543 |
| An Improved Method for Bandwidth Selection when Estimating ROC Curves |
0 |
0 |
0 |
138 |
3 |
7 |
9 |
564 |
| Anomaly Detection in High Dimensional Data |
0 |
1 |
1 |
27 |
2 |
6 |
9 |
89 |
| Anomaly detection in streaming nonstationary temporal data |
0 |
0 |
0 |
122 |
1 |
2 |
2 |
291 |
| Another Look at Measures of Forecast Accuracy |
3 |
9 |
20 |
1,534 |
13 |
54 |
113 |
4,007 |
| Automatic time series forecasting: the forecast package for R |
0 |
2 |
4 |
1,604 |
3 |
22 |
41 |
4,743 |
| Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation |
0 |
0 |
0 |
58 |
2 |
14 |
22 |
224 |
| Bandwidth Selection for Kernel Conditional Density Estimation |
0 |
0 |
0 |
0 |
0 |
3 |
3 |
3 |
| Bandwidth Selection for Kernel Conditional Density Estimation |
0 |
0 |
0 |
0 |
1 |
9 |
11 |
1,540 |
| Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC |
0 |
0 |
0 |
597 |
0 |
7 |
10 |
2,132 |
| Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC |
0 |
0 |
0 |
1,028 |
1 |
10 |
17 |
3,628 |
| Bayesian Rank Selection in Multivariate Regression |
0 |
0 |
0 |
51 |
1 |
7 |
14 |
107 |
| Boosting multi-step autoregressive forecasts |
0 |
0 |
0 |
78 |
5 |
11 |
14 |
142 |
| Calendar-based Graphics for Visualizing People's Daily Schedules |
0 |
0 |
0 |
4 |
7 |
16 |
16 |
57 |
| Coherent Mortality Forecasting The Product-ratio Method with Functional Time Series Models |
0 |
0 |
1 |
55 |
2 |
6 |
10 |
311 |
| Coherent Probabilistic Forecasts for Hierarchical Time Series |
0 |
0 |
0 |
85 |
3 |
6 |
10 |
199 |
| Coherent mortality forecasting: the product-ratio method with functional time series models |
0 |
0 |
0 |
67 |
2 |
5 |
9 |
196 |
| Conditional Normalization in Time Series Analysis |
0 |
0 |
2 |
24 |
2 |
6 |
13 |
34 |
| Cross-temporal Probabilistic Forecast Reconciliation |
0 |
0 |
0 |
23 |
3 |
11 |
13 |
27 |
| Density forecasting for long-term peak electricity demand |
0 |
0 |
1 |
226 |
2 |
6 |
11 |
606 |
| Detecting Distributional Differences between Temporal Granularities for Exploratory Time Series Analysis |
0 |
0 |
0 |
27 |
2 |
5 |
7 |
29 |
| Dimension Reduction For Outlier Detection Using DOBIN |
0 |
0 |
0 |
19 |
3 |
7 |
9 |
53 |
| Distributed ARIMA Models for Ultra-long Time Series |
0 |
0 |
0 |
115 |
0 |
6 |
13 |
194 |
| Efficient Identification of the Pareto Optimal Set |
0 |
0 |
0 |
13 |
0 |
3 |
4 |
97 |
| Efficient generation of time series with diverse and controllable characteristics |
0 |
0 |
1 |
69 |
1 |
9 |
13 |
211 |
| Empirical Information Criteria for Time Series Forecasting Model Selection |
0 |
0 |
0 |
1,000 |
2 |
8 |
9 |
3,404 |
| Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand |
0 |
0 |
0 |
769 |
0 |
4 |
7 |
2,853 |
| Exponential smoothing and non-negative data |
0 |
0 |
0 |
85 |
4 |
9 |
12 |
308 |
| FFORMA: Feature-based forecast model averaging |
1 |
2 |
5 |
130 |
3 |
12 |
26 |
571 |
| Fast Forecast Reconciliation Using Linear Models |
0 |
0 |
0 |
83 |
2 |
5 |
6 |
193 |
| Fast computation of reconciled forecasts for hierarchical and grouped time series |
0 |
0 |
0 |
63 |
1 |
7 |
10 |
148 |
| Forecast Linear AugmentedProjection (FLAP): A Free Lunch to Reduce Forecast Error Variance |
0 |
0 |
0 |
20 |
2 |
12 |
16 |
26 |
| Forecast Reconciliation: A Review |
0 |
1 |
2 |
25 |
3 |
11 |
23 |
51 |
| Forecast Reconciliation: A geometric View with New Insights on Bias Correction |
0 |
0 |
0 |
20 |
0 |
1 |
3 |
53 |
| Forecast Reconciliation: A geometric View with New Insights on Bias Correction |
0 |
0 |
0 |
29 |
1 |
5 |
8 |
42 |
| Forecasting Swiss Exports Using Bayesian Forecast Reconciliation |
0 |
0 |
0 |
45 |
6 |
15 |
21 |
71 |
| Forecasting Swiss Exports using Bayesian Forecast Reconciliation |
0 |
0 |
0 |
25 |
0 |
8 |
14 |
47 |
| Forecasting Time-Series with Correlated Seasonality |
0 |
1 |
1 |
263 |
0 |
9 |
11 |
780 |
| Forecasting age-related changes in breast cancer mortality among white and black US women: A functional approach |
0 |
0 |
0 |
36 |
0 |
2 |
2 |
213 |
| Forecasting age-specific breast cancer mortality using functional data models |
0 |
0 |
0 |
164 |
0 |
6 |
9 |
994 |
| Forecasting for Social Good |
0 |
0 |
0 |
24 |
0 |
7 |
10 |
147 |
| Forecasting hierarchical and grouped time series through trace minimization |
0 |
0 |
1 |
90 |
0 |
7 |
14 |
206 |
| Forecasting the Old-Age Dependency Ratio to Determine a Sustainable Pension Age |
0 |
6 |
7 |
34 |
4 |
17 |
22 |
298 |
| Forecasting time series with complex seasonal patterns using exponential smoothing |
0 |
1 |
3 |
222 |
2 |
11 |
30 |
595 |
| Forecasting with Temporal Hierarchies |
0 |
0 |
0 |
51 |
0 |
11 |
18 |
163 |
| Forecasting with Temporal Hierarchies |
0 |
0 |
0 |
74 |
0 |
6 |
12 |
257 |
| Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbourne's Rainfall |
0 |
0 |
0 |
251 |
0 |
7 |
7 |
1,570 |
| Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbourne's Rainfall |
0 |
0 |
0 |
0 |
0 |
2 |
2 |
2 |
| Grouped functional time series forecasting: An application to age-specific mortality rates |
0 |
0 |
1 |
72 |
0 |
5 |
7 |
124 |
| Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach |
0 |
0 |
0 |
188 |
0 |
3 |
6 |
910 |
| Hierarchical Forecasting |
0 |
0 |
0 |
106 |
1 |
9 |
19 |
239 |
| Hierarchical forecasts for Australian domestic tourism |
0 |
0 |
0 |
128 |
6 |
11 |
15 |
398 |
| Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach |
0 |
0 |
0 |
3 |
2 |
7 |
16 |
113 |
| Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach |
0 |
0 |
0 |
13 |
1 |
3 |
3 |
118 |
| Improving out-of-sample Forecasts of Stock Price Indexes with Forecast Reconciliation and Clustering |
0 |
0 |
1 |
27 |
1 |
4 |
11 |
40 |
| Invertibility Conditions for Exponential Smoothing Models |
0 |
0 |
1 |
418 |
0 |
7 |
10 |
2,647 |
| Leave-one-out Kernel Density Estimates for Outlier Detection |
0 |
0 |
1 |
18 |
10 |
16 |
27 |
82 |
| Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions |
0 |
0 |
0 |
212 |
1 |
6 |
10 |
796 |
| Local Linear Forecasts Using Cubic Smoothing Splines |
0 |
0 |
2 |
561 |
0 |
4 |
11 |
1,985 |
| Local Linear Multivariate Regression with Variable Bandwidth in the Presence of Heteroscedasticity |
0 |
0 |
0 |
199 |
1 |
8 |
10 |
736 |
| Long-term Forecasts of Age-specific Labour Market Participation Rates with Functional Data Models |
0 |
0 |
1 |
25 |
1 |
2 |
5 |
66 |
| Long-term forecasts of age-specific participation rates with functional data models |
0 |
0 |
0 |
37 |
0 |
8 |
11 |
86 |
| Low-dimensional decomposition, smoothing and forecasting of sparse functional data |
0 |
0 |
0 |
71 |
0 |
2 |
3 |
98 |
| Macroeconomic forecasting for Australia using a large number of predictors |
0 |
0 |
0 |
175 |
0 |
4 |
11 |
312 |
| Manifold Learning with Approximate Nearest Neighbors |
0 |
1 |
1 |
38 |
1 |
7 |
12 |
92 |
| Meta-learning how to forecast time series |
0 |
0 |
3 |
214 |
2 |
16 |
29 |
612 |
| Mixed Model-Based Hazard Estimation |
0 |
0 |
0 |
133 |
0 |
3 |
3 |
647 |
| Modelling and forecasting Australian domestic tourism |
0 |
0 |
2 |
380 |
2 |
7 |
12 |
939 |
| Monitoring Processes with Changing Variances |
0 |
0 |
1 |
61 |
1 |
5 |
10 |
180 |
| Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves |
0 |
0 |
0 |
234 |
1 |
4 |
7 |
1,216 |
| Non-linear exponential smoothing and positive data |
0 |
1 |
1 |
119 |
4 |
8 |
11 |
539 |
| Nonlinear Mixed Effects Models for Time Series Forecasting of Smart Meter Demand |
0 |
0 |
0 |
24 |
1 |
6 |
7 |
48 |
| Nonparametric Estimation and Symmetry Tests for Conditional Density Functions |
0 |
0 |
0 |
183 |
1 |
1 |
4 |
1,029 |
| Nonparametric autocovariance function estimation |
0 |
0 |
0 |
69 |
1 |
2 |
5 |
1,090 |
| Nonparametric estimation and symmetry tests for conditional density functions |
0 |
0 |
0 |
4 |
3 |
7 |
9 |
72 |
| Nonparametric time series forecasting with dynamic updating |
0 |
0 |
0 |
160 |
0 |
5 |
7 |
397 |
| On normalization and algorithm selection for unsupervised outlier detection |
0 |
0 |
0 |
36 |
0 |
4 |
7 |
93 |
| Online Conformal Inference for Multi-Step Time Series Forecasting |
0 |
3 |
8 |
59 |
1 |
13 |
30 |
112 |
| Optimal Forecast Reconciliation with Time Series Selection |
0 |
0 |
3 |
24 |
2 |
8 |
12 |
25 |
| Optimal Non-negative Forecast Reconciliation |
0 |
1 |
2 |
38 |
2 |
11 |
21 |
113 |
| Optimal combination forecasts for hierarchical time series |
0 |
0 |
1 |
286 |
2 |
10 |
22 |
698 |
| Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization |
0 |
2 |
8 |
68 |
2 |
14 |
43 |
177 |
| Prediction Intervals for Exponential Smoothing State Space Models |
0 |
0 |
2 |
639 |
3 |
9 |
17 |
2,159 |
| Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality |
0 |
0 |
0 |
52 |
2 |
6 |
8 |
50 |
| Probabilisitic forecasts in hierarchical time series |
0 |
1 |
1 |
62 |
3 |
7 |
10 |
142 |
| Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation |
0 |
0 |
0 |
53 |
0 |
7 |
18 |
122 |
| Probabilistic time series forecasting with boosted additive models: an application to smart meter data |
0 |
0 |
0 |
78 |
0 |
4 |
4 |
180 |
| Rainbow plots, Bagplots and Boxplots for Functional Data |
0 |
0 |
3 |
87 |
1 |
5 |
12 |
371 |
| Rating Forecasts for Television Programs |
0 |
0 |
0 |
223 |
0 |
4 |
9 |
647 |
| Recursive and direct multi-step forecasting: the best of both worlds |
0 |
7 |
27 |
465 |
6 |
38 |
122 |
1,411 |
| Residual Diagnostic Plots for Checking for Model Mis-Specification in Time Series Regression |
0 |
0 |
0 |
0 |
0 |
1 |
1 |
1 |
| Residual Diagnostic Plots for Checking for model Mis-Specification in Time Series Regression |
0 |
0 |
0 |
0 |
0 |
4 |
5 |
1,729 |
| Robust forecasting of mortality and fertility rates: a functional data approach |
0 |
1 |
2 |
431 |
1 |
7 |
17 |
1,242 |
| STR: A Seasonal-Trend Decomposition Procedure Based on Regression |
0 |
1 |
2 |
156 |
3 |
9 |
23 |
461 |
| Seasonal Functional Autoregressive Models |
0 |
0 |
1 |
42 |
0 |
7 |
13 |
82 |
| Short-term load forecasting based on a semi-parametric additive model |
1 |
1 |
2 |
76 |
5 |
7 |
13 |
238 |
| Some Nonlinear Exponential Smoothing Models are Unstable |
0 |
0 |
0 |
217 |
1 |
11 |
14 |
1,066 |
| Sparse Multiple Index Modelsfor High-dimensional Nonparametric Forecasting |
0 |
0 |
1 |
42 |
0 |
2 |
6 |
19 |
| Spatial modelling of the two-party preferred vote in Australian federal elections: 2001-2016 |
1 |
1 |
1 |
44 |
1 |
3 |
7 |
138 |
| Statistical Methodological Issues in Studies of Air Pollution and Respiratory Disease |
0 |
0 |
0 |
209 |
0 |
3 |
3 |
1,052 |
| Stochastic models underlying Croston's method for intermittent demand forecasting |
0 |
0 |
2 |
2,173 |
9 |
19 |
25 |
6,659 |
| Stochastic population forecasts using functional data models for mortality, fertility and migration |
0 |
1 |
4 |
267 |
1 |
5 |
14 |
877 |
| The Australian Macro Database: An Online Resource for Macroeconomic Research in Australia |
0 |
0 |
0 |
20 |
1 |
6 |
9 |
68 |
| The Australian Macro Database: An online resource for macroeconomic research in Australia |
0 |
0 |
0 |
38 |
1 |
5 |
6 |
88 |
| The Road to Recovery from COVID-19 for Australian Tourism |
0 |
0 |
3 |
67 |
1 |
3 |
11 |
152 |
| The price elasticity of electricity demand in South Australia |
0 |
0 |
1 |
187 |
3 |
8 |
13 |
487 |
| The tourism forecasting competition |
0 |
0 |
0 |
156 |
1 |
6 |
18 |
501 |
| The value of feedback in forecasting competitions |
0 |
0 |
1 |
60 |
0 |
10 |
17 |
213 |
| The vector innovation structural time series framework: a simple approach to multivariate forecasting |
0 |
0 |
0 |
180 |
1 |
8 |
9 |
505 |
| Time Series Forecasting: The Case for the Single Source of Error State Space |
0 |
0 |
0 |
335 |
1 |
8 |
8 |
1,309 |
| Two-dimensional smoothing of mortality rates |
0 |
1 |
1 |
34 |
0 |
5 |
11 |
109 |
| Unmasking the Theta Method |
0 |
0 |
1 |
311 |
0 |
6 |
16 |
1,235 |
| Using R to Teach Econometrics |
0 |
0 |
1 |
2,177 |
2 |
14 |
16 |
4,422 |
| Visualising forecasting Algorithm Performance using Time Series Instance Spaces |
0 |
0 |
1 |
108 |
1 |
7 |
14 |
153 |
| Visualizing Probability Distributions across Bivariate Cyclic Temporal Granularities |
0 |
0 |
0 |
0 |
3 |
6 |
7 |
14 |
| Total Working Papers |
7 |
49 |
163 |
25,237 |
205 |
976 |
1,742 |
83,567 |
| 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 |
1 |
2 |
260 |
3 |
12 |
31 |
973 |
| A Bayesian approach to bandwidth selection for multivariate kernel density estimation |
0 |
0 |
0 |
107 |
3 |
7 |
9 |
329 |
| A brief history of forecasting competitions |
0 |
0 |
1 |
32 |
0 |
5 |
15 |
146 |
| A change of editors |
0 |
0 |
0 |
7 |
1 |
5 |
7 |
72 |
| A gradient boosting approach to the Kaggle load forecasting competition |
0 |
1 |
1 |
56 |
1 |
10 |
26 |
331 |
| A multivariate innovations state space Beveridge-Nelson decomposition |
0 |
0 |
0 |
33 |
2 |
8 |
10 |
175 |
| A note on the categorization of demand patterns |
1 |
1 |
1 |
6 |
5 |
11 |
17 |
43 |
| A note on the validity of cross-validation for evaluating autoregressive time series prediction |
3 |
10 |
30 |
284 |
22 |
82 |
158 |
832 |
| A note on upper bounds for forecast-value-added relative to naïve forecasts |
0 |
0 |
0 |
2 |
1 |
3 |
3 |
45 |
| A state space framework for automatic forecasting using exponential smoothing methods |
3 |
4 |
14 |
272 |
8 |
25 |
71 |
952 |
| Another Look at Forecast Accuracy Metrics for Intermittent Demand |
1 |
2 |
6 |
403 |
3 |
13 |
41 |
1,499 |
| Another look at measures of forecast accuracy |
5 |
13 |
33 |
469 |
19 |
66 |
148 |
1,688 |
| Assessing mortality inequality in the U.S.: What can be said about the future? |
0 |
0 |
0 |
3 |
2 |
5 |
11 |
21 |
| Automatic Time Series Forecasting: The forecast Package for R |
0 |
1 |
2 |
483 |
7 |
24 |
54 |
2,316 |
| Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation |
1 |
1 |
3 |
48 |
2 |
12 |
32 |
220 |
| Bandwidth selection for kernel conditional density estimation |
0 |
0 |
7 |
119 |
0 |
4 |
27 |
360 |
| Call for Papers: Special issue of the International Journal of Forecasting on tourism forecasting |
0 |
0 |
0 |
28 |
0 |
2 |
3 |
240 |
| Changing of the guard |
0 |
0 |
0 |
3 |
2 |
4 |
5 |
46 |
| Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models |
0 |
0 |
0 |
20 |
3 |
11 |
13 |
150 |
| Comments on: Exploratory functional data analysis |
0 |
0 |
0 |
0 |
1 |
9 |
10 |
10 |
| Cross-temporal probabilistic forecast reconciliation: Methodological and practical issues |
0 |
1 |
1 |
2 |
1 |
8 |
11 |
13 |
| Crude oil price forecasting based on internet concern using an extreme learning machine |
0 |
0 |
0 |
22 |
0 |
4 |
10 |
99 |
| Distributed ARIMA models for ultra-long time series |
0 |
0 |
2 |
6 |
1 |
2 |
9 |
26 |
| Dynamic algorithm selection for pareto optimal set approximation |
0 |
0 |
0 |
6 |
3 |
11 |
16 |
42 |
| Early classification of spatio-temporal events using partial information |
0 |
0 |
0 |
0 |
0 |
3 |
6 |
12 |
| Editorial |
0 |
0 |
0 |
9 |
0 |
2 |
2 |
118 |
| Encouraging replication and reproducible research |
0 |
0 |
0 |
16 |
1 |
3 |
7 |
86 |
| Errors on Percentage Errors |
1 |
1 |
4 |
4 |
3 |
8 |
15 |
15 |
| Exploring the sources of uncertainty: Why does bagging for time series forecasting work? |
0 |
1 |
2 |
23 |
0 |
12 |
18 |
103 |
| Exponential smoothing models: Means and variances for lead-time demand |
0 |
0 |
0 |
27 |
2 |
6 |
10 |
172 |
| FFORMA: Feature-based forecast model averaging |
0 |
2 |
12 |
51 |
2 |
15 |
44 |
248 |
| Fast computation of reconciled forecasts for hierarchical and grouped time series |
0 |
0 |
0 |
6 |
2 |
6 |
8 |
66 |
| Forecast combinations: An over 50-year review |
1 |
1 |
11 |
33 |
5 |
33 |
70 |
118 |
| Forecast reconciliation: A geometric view with new insights on bias correction |
1 |
1 |
3 |
13 |
4 |
16 |
27 |
75 |
| Forecast reconciliation: A review |
0 |
0 |
7 |
12 |
5 |
21 |
59 |
77 |
| Forecasting Swiss exports using Bayesian forecast reconciliation |
0 |
0 |
0 |
5 |
0 |
7 |
10 |
32 |
| Forecasting for social good |
0 |
1 |
2 |
4 |
1 |
10 |
19 |
28 |
| Forecasting in social settings: The state of the art |
0 |
3 |
7 |
22 |
6 |
18 |
29 |
125 |
| Forecasting interrupted time series |
0 |
1 |
2 |
2 |
2 |
11 |
19 |
19 |
| Forecasting time series with multiple seasonal patterns |
0 |
0 |
1 |
188 |
2 |
7 |
11 |
674 |
| Forecasting with temporal hierarchies |
0 |
2 |
5 |
25 |
1 |
13 |
38 |
128 |
| Forecasting, causality and feedback |
0 |
0 |
0 |
9 |
1 |
3 |
4 |
25 |
| Free Open-Source Forecasting Using R |
0 |
0 |
1 |
168 |
0 |
4 |
8 |
498 |
| Half-life estimation based on the bias-corrected bootstrap: A highest density region approach |
0 |
0 |
0 |
41 |
0 |
5 |
7 |
229 |
| Hierarchical Probabilistic Forecasting of Electricity Demand With Smart Meter Data |
1 |
1 |
5 |
10 |
4 |
9 |
23 |
44 |
| Hierarchical forecasts for Australian domestic tourism |
0 |
0 |
2 |
101 |
2 |
14 |
24 |
421 |
| Improved interval estimation of long run response from a dynamic linear model: A highest density region approach |
0 |
0 |
0 |
11 |
0 |
7 |
12 |
137 |
| Improved methods for bandwidth selection when estimating ROC curves |
0 |
0 |
0 |
11 |
0 |
7 |
7 |
90 |
| Improving out-of-sample forecasts of stock price indexes with forecast reconciliation and clustering |
0 |
0 |
1 |
1 |
0 |
3 |
8 |
8 |
| Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions |
0 |
0 |
0 |
70 |
1 |
7 |
8 |
465 |
| LoMEF: A framework to produce local explanations for global model time series forecasts |
0 |
0 |
0 |
1 |
1 |
5 |
10 |
19 |
| MSTL: a seasonal-trend decomposition algorithm for time series with multiple seasonal patterns |
0 |
0 |
7 |
7 |
2 |
5 |
27 |
29 |
| Macroeconomic forecasting for Australia using a large number of predictors |
0 |
0 |
2 |
8 |
5 |
12 |
25 |
63 |
| Minimum Sample Size requirements for Seasonal Forecasting Models |
0 |
1 |
6 |
220 |
7 |
25 |
51 |
1,133 |
| Modern Strategies for Time Series Regression |
0 |
0 |
1 |
1 |
3 |
9 |
12 |
22 |
| Monitoring processes with changing variances |
0 |
0 |
0 |
20 |
0 |
5 |
8 |
129 |
| Nonparametric time series forecasting with dynamic updating |
0 |
0 |
0 |
3 |
1 |
4 |
12 |
67 |
| Non‐linear mixed‐effects models for time series forecasting of smart meter demand |
0 |
0 |
2 |
5 |
3 |
8 |
11 |
23 |
| On continuous-time threshold autoregression |
0 |
0 |
0 |
51 |
2 |
5 |
7 |
181 |
| Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization |
0 |
0 |
14 |
33 |
10 |
24 |
58 |
146 |
| Optimal combination forecasts for hierarchical time series |
0 |
1 |
3 |
87 |
3 |
14 |
36 |
404 |
| Optimal forecast reconciliation with time series selection |
0 |
0 |
1 |
1 |
4 |
23 |
28 |
28 |
| Optimally Reconciling Forecasts in a Hierarchy |
0 |
0 |
1 |
172 |
1 |
9 |
17 |
444 |
| Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods |
0 |
0 |
0 |
20 |
0 |
12 |
16 |
152 |
| Predicting sediment and nutrient concentrations from high-frequency water-quality data |
0 |
0 |
0 |
0 |
0 |
3 |
6 |
12 |
| Prediction intervals for exponential smoothing using two new classes of state space models |
0 |
0 |
1 |
151 |
0 |
7 |
12 |
592 |
| Principles and algorithms for forecasting groups of time series: Locality and globality |
0 |
1 |
6 |
12 |
5 |
20 |
61 |
106 |
| Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond |
0 |
2 |
17 |
156 |
8 |
25 |
66 |
603 |
| Probabilistic forecast reconciliation: Properties, evaluation and score optimisation |
0 |
0 |
2 |
9 |
1 |
9 |
21 |
44 |
| Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters |
0 |
0 |
1 |
1 |
2 |
6 |
8 |
10 |
| Robust forecasting of mortality and fertility rates: A functional data approach |
0 |
1 |
11 |
372 |
13 |
26 |
58 |
1,036 |
| STR: Seasonal-Trend Decomposition Using Regression |
0 |
2 |
3 |
13 |
1 |
14 |
25 |
84 |
| Seasonal functional autoregressive models |
0 |
0 |
1 |
5 |
1 |
3 |
15 |
33 |
| Smoothing non-Gaussian time series with autoregressive structure |
0 |
0 |
0 |
29 |
1 |
7 |
7 |
189 |
| Some Properties and Generalizations of Non‐negative Bayesian Time Series Models |
0 |
0 |
0 |
0 |
3 |
9 |
12 |
19 |
| Stochastic models underlying Croston's method for intermittent demand forecasting |
0 |
0 |
3 |
506 |
1 |
11 |
24 |
1,901 |
| Stochastic population forecasts using functional data models for mortality, fertility and migration |
0 |
1 |
8 |
149 |
2 |
11 |
24 |
427 |
| The admissible parameter space for exponential smoothing models |
0 |
0 |
0 |
89 |
1 |
15 |
17 |
261 |
| The interaction between trend and seasonality |
0 |
0 |
0 |
84 |
0 |
5 |
6 |
341 |
| The price elasticity of electricity demand in South Australia |
0 |
0 |
5 |
120 |
2 |
5 |
19 |
443 |
| The tourism forecasting competition |
0 |
0 |
1 |
55 |
0 |
7 |
19 |
437 |
| The tourism forecasting competition |
0 |
0 |
1 |
27 |
2 |
9 |
13 |
201 |
| The value of feedback in forecasting competitions |
0 |
0 |
0 |
5 |
0 |
3 |
5 |
80 |
| The value of feedback in forecasting competitions |
0 |
0 |
0 |
12 |
1 |
6 |
11 |
142 |
| Tourism forecasting: An introduction |
0 |
0 |
1 |
50 |
7 |
16 |
19 |
172 |
| Twenty-five years of forecasting |
0 |
0 |
0 |
64 |
0 |
9 |
12 |
192 |
| Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data |
0 |
0 |
0 |
0 |
0 |
4 |
6 |
6 |
| Unmasking the Theta method |
0 |
1 |
1 |
82 |
4 |
9 |
17 |
435 |
| Using R to teach econometrics |
0 |
0 |
1 |
1,489 |
2 |
7 |
13 |
3,489 |
| Visualising forecasting algorithm performance using time series instance spaces |
0 |
0 |
1 |
31 |
2 |
5 |
10 |
156 |
| YULE‐WALKER ESTIMATES FOR CONTINUOUS‐TIME AUTOREGRESSIVE MODELS |
0 |
0 |
0 |
6 |
1 |
2 |
4 |
22 |
| Total Journal Articles |
18 |
59 |
269 |
7,679 |
236 |
1,006 |
2,058 |
28,914 |