Rob J Hyndman : Citation Profile

Are you Rob J Hyndman?

Monash University

29

H index

51

i10 index

3704

Citations

RESEARCH PRODUCTION:

77

Articles

111

Papers

1

Chapters

EDITOR:

1

Series edited

RESEARCH ACTIVITY:

   31 years (1992 - 2023). See details.
   Cites by year: 119
   Journals where Rob J Hyndman has often published
   Relations with other researchers
   Recent citing documents: 490.    Total self citations: 113 (2.96 %)

EXPERT IN:

   Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
   Demographic Trends, Macroeconomic Effects, and Forecasts
   Semiparametric and Nonparametric Methods: General

MORE DETAILS IN:
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   Permalink: http://citec.repec.org/phy3
   Updated: 2023-11-04    RAS profile: 2023-01-18    
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Relations with other researchers

Works with:

Athanasopoulos, George (12)

Panagiotelis, Anastasios (7)

Li, Feng (2)

Talagala, Priyanga (2)

Eckert, Florian (2)

Authors registered in RePEc who have co-authored more than one work in the last five years with Rob J Hyndman.

Is cited by:

Shang, Han Lin (105)

Li, Feng (77)

Athanasopoulos, George (59)

Nikolopoulos, Konstantinos (52)

Weron, Rafał (50)

Castle, Jennifer (39)

Hendry, David (37)

Franses, Philip Hans (33)

Grossi, Luigi (31)

Thomakos, Dimitrios (30)

Guidolin, Massimo (29)

Cites to:

Snyder, Ralph (84)

Athanasopoulos, George (74)

Ord, Keith (52)

Shang, Han Lin (32)

Nikolopoulos, Konstantinos (20)

Lee, Ronald (20)

Engle, Robert (17)

Diebold, Francis (16)

Franses, Philip Hans (15)

Panagiotelis, Anastasios (13)

Hong, Tao (12)

Main data

Where Rob J Hyndman has published?

Journals with more than one article published# docs
International Journal of Forecasting32
Computational Statistics & Data Analysis9
European Journal of Operational Research6
Foresight: The International Journal of Applied Forecasting4
Journal of Time Series Analysis2
Journal of the Operational Research Society2
Journal of the American Statistical Association2
Demographic Research2
Journal of Forecasting2
PLOS ONE2

Working Papers Series with more than one paper published# docs
Monash Econometrics and Business Statistics Working Papers / Monash University, Department of Econometrics and Business Statistics100

Recent works citing Rob J Hyndman (2023 and 2022)

YearTitle of citing document
2022Comparative Analysis of ARIMA and Artificial Neural Network Techniques for Forecasting Non-Stationary Agricultural Output Time Series. (2022). Dias, Ronaldo ; Awe, Olushina Olawale. In: AGRIS on-line Papers in Economics and Informatics. RePEc:ags:aolpei:330100.

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2022Forecasting agricultural commodity price using different models: a case study of widely consumed grains in Nigeria. (2022). Tabash, Mosab I ; Adeeko, Omotara ; Safi, Samir K ; Sanusi, Olajide I. In: Agricultural and Resource Economics: International Scientific E-Journal. RePEc:ags:areint:322724.

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2022The ABARES Approach to Forecasting Agricultural Commodity Markets. (2022). Gooday, Peter ; Xia, Charley ; Cameron, Andrew ; Nelson, Rohan. In: Australasian Agribusiness Review. RePEc:ags:auagre:335271.

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2022Enabling Users to Evaluate the Accuracy of ABARES Agricultural Forecasts. (2022). Nelson, Rohan ; Cameron, Andrew. In: Australasian Agribusiness Review. RePEc:ags:auagre:335272.

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2022Impact of the Global COVID-19 Pandemic on FDI: Evidence from a Small Open Economy. (2022). Teeroovengadum, Viraiyan ; Fauzel, Sheereen ; Tandrayen-Ragoobur, Verena ; Seetanah, Boopen ; Jaffur, Zameelah Khan. In: Conference papers. RePEc:ags:pugtwp:333443.

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2023Combined Forecasts of Intermittent Demand for Stock-keeping Units (SKUs). (2023). Utma, Gizem Halil ; Ikiz, Aysun Kapucugil. In: World Journal of Applied Economics. RePEc:ana:journl:v:9:y:2023:i:1:p:1-31.

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2023Time Series Forecasting of the Covid-19 Pandemic: A Critical Assessment in Retrospect. (2023). Gungor, Murat. In: Alphanumeric Journal. RePEc:anm:alpnmr:v:11:y:2023:i:1:p:85-100.

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2023Deep Dynamic Factor Models. (2020). Ricco, Giovanni ; Izzo, Cosimo ; Andreini, Paolo. In: Papers. RePEc:arx:papers:2007.11887.

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2023Time-Varying Parameters as Ridge Regressions. (2020). Coulombe, Philippe Goulet. In: Papers. RePEc:arx:papers:2009.00401.

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2022High Dimensional Forecast Combinations Under Latent Structures. (2020). Su, Liangjun ; Shi, Zhentao ; Xie, Tian. In: Papers. RePEc:arx:papers:2010.09477.

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2022Forecasting Quarterly Brazilian GDP: Univariate Models Approach. (2020). Coelho, Felipe Leite ; Sales, Kleyton Vieira ; da Silva, Josiane. In: Papers. RePEc:arx:papers:2010.13259.

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2023Functional Principal Component Analysis of Cointegrated Functional Time Series. (2020). Seo, Won-Ki. In: Papers. RePEc:arx:papers:2011.12781.

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2022Bayesian forecast combination using time-varying features. (2021). Li, Feng ; Kang, Yanfei. In: Papers. RePEc:arx:papers:2108.02082.

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2022The DONUT Approach to EnsembleCombination Forecasting. (2022). Krange, Kjartan ; Ankile, Lars Lien. In: Papers. RePEc:arx:papers:2201.00426.

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2022Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction. (2022). Salish, Nazarii ; Otto, Sven. In: Papers. RePEc:arx:papers:2201.02532.

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2022Predicting Default Probabilities for Stress Tests: A Comparison of Models. (2022). Guth, Martin. In: Papers. RePEc:arx:papers:2202.03110.

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2023Scarring effects of the COVID-19 pandemic on the Italian labour market. (2022). Fiaschi, Davide ; Tealdi, Cristina. In: Papers. RePEc:arx:papers:2202.13317.

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2022Feature-based intermittent demand forecast combinations: bias, accuracy and inventory implications. (2022). Li, Feng ; Petropoulos, Fotios ; Kang, Yanfei. In: Papers. RePEc:arx:papers:2204.08283.

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2022Optimal reconciliation with immutable forecasts. (2022). Li, Feng ; Panagiotelis, Anastasios ; Kang, Yanfei ; Zhang, Bohan. In: Papers. RePEc:arx:papers:2204.09231.

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2022Forecasting Electricity Prices. (2022). Weron, Rafał ; Uniejewski, Bartosz ; Maciejowska, Katarzyna. In: Papers. RePEc:arx:papers:2204.11735.

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2022A Market for Trading Forecasts: A Wagering Mechanism. (2022). Grammatico, Sergio ; Kazempour, Jalal ; Pinson, Pierre ; Raja, Aitazaz Ali. In: Papers. RePEc:arx:papers:2205.02668.

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2022Nowcasting the Portuguese GDP with Monthly Data. (2022). Fernandes, Pedro Afonso ; Assunccao, Joao B. In: Papers. RePEc:arx:papers:2206.06823.

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2022Distributional neural networks for electricity price forecasting. (2022). Ziel, Florian ; Weron, Rafal ; Narajewski, Michal ; Marcjasz, Grzegorz. In: Papers. RePEc:arx:papers:2207.02832.

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2022Application of Hawkes volatility in the observation of filtered high-frequency price process in tick structures. (2022). Lee, Kyungsub. In: Papers. RePEc:arx:papers:2207.05939.

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2023Global combinations of expert forecasts. (2022). Vasnev, Andrey L ; Thompson, Ryan ; Qian, Yilin. In: Papers. RePEc:arx:papers:2207.07318.

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2022Macroeconomic Predictions using Payments Data and Machine Learning. (2022). Desai, Ajit ; James, . In: Papers. RePEc:arx:papers:2209.00948.

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2022Causal Effect Estimation with Global Probabilistic Forecasting: A Case Study of the Impact of Covid-19 Lockdowns on Energy Demand. (2022). Bergmeir, Christoph ; Weng, Angela Dieyu ; Grecov, Priscila ; Prasanna, Ankitha Nandipura. In: Papers. RePEc:arx:papers:2209.08885.

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2023Predicting Performances of Mutual Funds using Deep Learning and Ensemble Techniques. (2022). Tran, Hien ; Nguyen, Huy ; Pham, Nga ; Dao, Binh ; Chu, Nghia. In: Papers. RePEc:arx:papers:2209.09649.

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2022DNN-ForwardTesting: A New Trading Strategy Validation using Statistical Timeseries Analysis and Deep Neural Networks. (2022). Dyoub, Abeer ; de Gasperis, Giovanni ; della Penna, Giuseppe ; Letteri, Ivan. In: Papers. RePEc:arx:papers:2210.11532.

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2023Prediction intervals for economic fixed-event forecasts. (2022). Plett, Hendrik ; Kruger, Fabian. In: Papers. RePEc:arx:papers:2210.13562.

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2022Spatio-temporal Event Studies for Air Quality Assessment under Cross-sectional Dependence. (2022). Pelagatti, Matteo Maria ; Maranzano, Paolo. In: Papers. RePEc:arx:papers:2210.17529.

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2023Reservoir Computing for Macroeconomic Forecasting with Mixed Frequency Data. (2022). Ortega, Juan-Pablo ; van Huellen, Sophie ; Hirt, Marcel ; Grigoryeva, Lyudmila ; Dellaportas, Petros ; Ballarin, Giovanni. In: Papers. RePEc:arx:papers:2211.00363.

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2023Copula Variational LSTM for High-dimensional Cross-market Multivariate Dependence Modeling. (2023). Cao, Longbing ; Xu, Jia. In: Papers. RePEc:arx:papers:2305.08778.

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2023Machine Learning for Socially Responsible Portfolio Optimisation. (2023). van Zyl, Terence L ; Nundlall, Taeisha. In: Papers. RePEc:arx:papers:2305.12364.

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2023Hierarchical forecasting for aggregated curves with an application to day-ahead electricity price auctions. (2023). Ziel, Florian ; Ghelasi, Paul. In: Papers. RePEc:arx:papers:2305.16255.

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2023Not feeling the buzz: Correction study of mispricing and inefficiency in online sportsbooks. (2023). Cartlidge, John ; Clegg, Lawrence. In: Papers. RePEc:arx:papers:2306.01740.

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2023Maximally Machine-Learnable Portfolios. (2023). Goebel, Maximilian ; Coulombe, Philippe Goulet. In: Papers. RePEc:arx:papers:2306.05568.

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2023Noise reduction for functional time series. (2023). Wouters, Bram ; Diks, Cees. In: Papers. RePEc:arx:papers:2307.02154.

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2023Exploring the Dynamics of the Specialty Insurance Market Using a Novel Discrete Event Simulation Framework: a Lloyds of London Case Study. (2023). Tua, Alan ; Feng, Zhe ; Kam, Keith ; Ahmed, Akhil ; Olmez, Sedar. In: Papers. RePEc:arx:papers:2307.05581.

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2023Comparative Analysis of Machine Learning, Hybrid, and Deep Learning Forecasting Models Evidence from European Financial Markets and Bitcoins. (2023). Ampountolas, Apostolos. In: Papers. RePEc:arx:papers:2307.08853.

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2023The Bayesian Context Trees State Space Model for time series modelling and forecasting. (2023). Kontoyiannis, Ioannis ; Papageorgiou, Ioannis. In: Papers. RePEc:arx:papers:2308.00913.

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2023Econometrics of Machine Learning Methods in Economic Forecasting. (2023). Striaukas, Jonas ; Ghysels, Eric ; Babii, Andrii. In: Papers. RePEc:arx:papers:2308.10993.

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2023Hedging Forecast Combinations With an Application to the Random Forest. (2023). Wolf, Michael ; Kozbur, Damian ; Beck, Elliot. In: Papers. RePEc:arx:papers:2308.15384.

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2022Performance of 109 Machine Learning Algorithms across Five Forecasting Tasks: Employee Behavior Modeling, Online Communication, House Pricing, IT Support and Demand Planning. (2022). Gerunov, Anton A. In: Economic Studies journal. RePEc:bas:econst:y:2022:i:2:p:15-43.

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2023.

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2022Macroeconomic Predictions Using Payments Data and Machine Learning. (2022). Desai, Ajit ; Chapman, James. In: Staff Working Papers. RePEc:bca:bocawp:22-10.

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2023A tool to nowcast tourist overnight stays with payment data and complementary indicators. (2023). Mariani, Vincenzo ; Crispino, Marta. In: Questioni di Economia e Finanza (Occasional Papers). RePEc:bdi:opques:qef_746_23.

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2022Stock return predictability: Evaluation based on interval forecasts. (2022). Kim, Jae H ; Darne, Olivier ; Charles, Amelie. In: Bulletin of Economic Research. RePEc:bla:buecrs:v:74:y:2022:i:2:p:363-385.

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2022Dynamic modelling of mortality via mixtures of skewed distribution functions. (2022). Scarpa, Bruno ; Mazzuco, Stefano ; Aliverti, Emanuele. In: Journal of the Royal Statistical Society Series A. RePEc:bla:jorssa:v:185:y:2022:i:3:p:1030-1048.

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2022Long?term prediction intervals with many covariates. (2022). Wu, Wei Biao ; Chud, Marek ; Karmakar, Sayar. In: Journal of Time Series Analysis. RePEc:bla:jtsera:v:43:y:2022:i:4:p:587-609.

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2022Do job vacancies variations anticipate employment variations by sector? Some preliminary evidence from Italy. (2022). Lovaglio, Pietro Giorgio. In: LABOUR. RePEc:bla:labour:v:36:y:2022:i:1:p:71-93.

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2022The negative binomial process: A tractable model with composite likelihood?based inference. (2022). Ombao, Hernando ; Barretosouza, Wagner. In: Scandinavian Journal of Statistics. RePEc:bla:scjsta:v:49:y:2022:i:2:p:568-592.

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2023Recent developments in multivariate wind and solar power forecasting. (2023). Madsen, Henrik ; Bacher, Peder ; Moller, Jan K ; Bjerregrd, Mathias B ; Nystrup, Peter ; Sorensen, Mikkel L. In: Wiley Interdisciplinary Reviews: Energy and Environment. RePEc:bla:wireae:v:12:y:2023:i:2:n:e465.

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2022Forecasting actuarial time series: a practical study of the effect of statistical pre-adjustments. (2022). Sagianou, Aliki ; Hatzopoulos, Peter ; Galanopoulos, Nikolaos G ; Milionis, Alexandros E. In: Working Papers. RePEc:bog:wpaper:297.

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2023Parameter least-squares estimation for time-inhomogeneous Ornstein–Uhlenbeck process. (2023). Getut, Pramesti. In: Monte Carlo Methods and Applications. RePEc:bpj:mcmeap:v:29:y:2023:i:1:p:1-32:n:5.

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2023The Human Multiple Births Database (HMBD). (2023). Pison, Gilles ; Caporali, Arianna ; Torres, Catalina. In: Demographic Research. RePEc:dem:demres:v:48:y:2023:i:4.

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2023A validation workflow for mortality forecasting. (2023). Bohk-Ewald, Christina ; Scholey, Jonas ; Duerst, Ricarda. In: MPIDR Working Papers. RePEc:dem:wpaper:wp-2023-020.

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2023Volatile Financial Conditions, Asset Prices, and Investment Decisions: Analysis of daily data of DJIA and S&P500, from January to April of 2022. (2023). Pemberton, Jared. In: Applied Econometrics and International Development. RePEc:eaa:aeinde:v:23:y:2023:i:1_5.

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2023Analyzing Electricity Demand in Colombia: A Functional Time Series Approach. (2023). Duque, Fernando Villada ; Marulanda, Laura Marquez ; Marin, Jorge Barrientos. In: International Journal of Energy Economics and Policy. RePEc:eco:journ2:2023-01-11.

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2022Forecasting tourism growth with State-Dependent Models. (2022). Heravi, Saeed ; Hassani, Hossein ; Silva, Emmanuel Sirimal ; Guan, BO. In: Annals of Tourism Research. RePEc:eee:anture:v:94:y:2022:i:c:s0160738322000366.

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2022‘Modelling’ UK tourism demand using fashion retail sales. (2022). Hassani, Hossein ; Silva, Emmanuel Sirimal. In: Annals of Tourism Research. RePEc:eee:anture:v:95:y:2022:i:c:s0160738322000792.

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2022A deep generative model for probabilistic energy forecasting in power systems: normalizing flows. (2022). Cornelusse, Bertrand ; Lanaspeze, Damien ; Wehenkel, Antoine ; Dumas, Jonathan ; Sutera, Antonio. In: Applied Energy. RePEc:eee:appene:v:305:y:2022:i:c:s0306261921011909.

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2022Resource-optimised generation dispatch strategy for district heating systems using dynamic hierarchical optimisation. (2022). Blum, Martin ; Hammacher, Jorg ; Mosbach, Sebastian ; Hofmeister, Markus ; Kraft, Markus ; Bhave, Amit ; Flegel, Volker ; Dorr, Christoph ; Rohrig, Gerd. In: Applied Energy. RePEc:eee:appene:v:305:y:2022:i:c:s0306261921011958.

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2022Framework for collaborative intelligence in forecasting day-ahead electricity price. (2022). Yeregui, Imanol ; Naveran, Gorka ; Irizar, Ion ; Castro, Alain ; Beltran, Sergio. In: Applied Energy. RePEc:eee:appene:v:306:y:2022:i:pa:s0306261921013398.

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2022Probabilistic electric load forecasting through Bayesian Mixture Density Networks. (2022). Vitali, Andrea ; Spinelli, Stefano ; Matteucci, Matteo ; Brusaferri, Alessandro. In: Applied Energy. RePEc:eee:appene:v:309:y:2022:i:c:s0306261921015907.

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2022Change point detection-based simulation of nonstationary sub-hourly wind time series. (2022). Sundararajan, Raanju R ; Gangammanavar, Harsha ; Ariyarathne, Sakitha. In: Applied Energy. RePEc:eee:appene:v:310:y:2022:i:c:s0306261921017165.

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2022Short-term hydropower optimization driven by innovative time-adapting econometric model. (2022). Majone, Bruno ; Righetti, Maurizio ; Ravazzolo, Francesco ; Galletti, Andrea ; di Marco, Nicola ; Zanfei, Ariele ; Avesani, Diego. In: Applied Energy. RePEc:eee:appene:v:310:y:2022:i:c:s0306261921017244.

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2022Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization. (2022). Wang, Lin ; Lv, Sheng-Xiang. In: Applied Energy. RePEc:eee:appene:v:311:y:2022:i:c:s0306261922001404.

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2022Electricity price forecasting on the day-ahead market using machine learning. (2022). Robardet, Celine ; Plantevit, Marc ; Pierre, Erwan ; Tschora, Leonard. In: Applied Energy. RePEc:eee:appene:v:313:y:2022:i:c:s0306261922002057.

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2022Review and prospect of data-driven techniques for load forecasting in integrated energy systems. (2022). , Lei ; Huang, Yanting ; Li, Shenglin ; Zheng, Weiye ; Dong, Hanjiang ; Zhu, Jizhong. In: Applied Energy. RePEc:eee:appene:v:321:y:2022:i:c:s0306261922006262.

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2022Nonparametric probabilistic load forecasting based on quantile combination in electrical power systems. (2022). Fu, Hong ; Wang, Shuo ; Cao, Chaojin ; He, Yaoyao. In: Applied Energy. RePEc:eee:appene:v:322:y:2022:i:c:s0306261922008273.

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2022Accuracy indicators for evaluating retrospective performance of energy system models. (2022). Trutnevyte, Evelina ; Jaxa-Rozen, Marc ; Wen, Xin. In: Applied Energy. RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011667.

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2022Optimization-driven uncertainty forecasting: Application to day-ahead commitment with renewable energy resources. (2022). Kwon, Soongeol ; Karimi, Sajad. In: Applied Energy. RePEc:eee:appene:v:326:y:2022:i:c:s0306261922011862.

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2022Cloud-based model-predictive-control of a battery storage system at a commercial site. (2022). Grimeland, M ; Peristy, M ; Moore, T ; Goldsworthy, M. In: Applied Energy. RePEc:eee:appene:v:327:y:2022:i:c:s0306261922012958.

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2022An interpretable forecasting framework for energy consumption and CO2 emissions. (2022). Van, Hanifi M ; Aras, Serkan. In: Applied Energy. RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014209.

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2022Point and interval forecasting system for crude oil price based on complete ensemble extreme-point symmetric mode decomposition with adaptive noise and intelligent optimization algorithm. (2022). Li, Shaoting ; Wang, Xuerui. In: Applied Energy. RePEc:eee:appene:v:328:y:2022:i:c:s0306261922014519.

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2023Dynamic ensemble deep echo state network for significant wave height forecasting. (2023). Suganthan, Ponnuthurai Nagaratnam ; Hu, Minghui ; Li, Ruilin ; Gao, Ruobin ; Yuen, Kum Fai. In: Applied Energy. RePEc:eee:appene:v:329:y:2023:i:c:s0306261922015185.

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2023A proactive 2-stage indoor CO2-based demand-controlled ventilation method considering control performance and energy efficiency. (2023). Li, Ming ; Cui, Can. In: Applied Energy. RePEc:eee:appene:v:329:y:2023:i:c:s0306261922015458.

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2023Short-term electricity load forecasting—A systematic approach from system level to secondary substations. (2023). Francisco, Alexandre P ; Madeira, Sara C ; Pinheiro, Marco G. In: Applied Energy. RePEc:eee:appene:v:332:y:2023:i:c:s0306261922017500.

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2023Conformal asymmetric multi-quantile generative transformer for day-ahead wind power interval prediction. (2023). Guo, Chuangxin ; Huang, Gang ; Feng, Bin ; Wang, Wei ; Chen, Zhe ; Liao, Wenlong. In: Applied Energy. RePEc:eee:appene:v:333:y:2023:i:c:s0306261922018918.

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2023Can grid-tied solar photovoltaics lead to residential heating electrification? A techno-economic case study in the midwestern U.S.. (2023). Pearce, Joshua M ; Sommerfeldt, Nelson. In: Applied Energy. RePEc:eee:appene:v:336:y:2023:i:c:s0306261923002027.

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2023Optimal dispatch of a multi-energy system microgrid under uncertainty: A renewable energy community in Austria. (2023). Haas, Reinhard ; Ajanovic, Amela ; Auer, Hans ; Zellinger, Michael ; Mansoor, Muhammad ; Stadler, Michael ; Cosic, Armin ; Houben, Nikolaus. In: Applied Energy. RePEc:eee:appene:v:337:y:2023:i:c:s0306261923002775.

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2023Grid-connected cabin preheating of Electric Vehicles in cold climates – A non-flexible share of the EV energy use. (2023). Andresen, Inger ; Ludvigsen, Bjorn ; Sorensen, Se Lekang. In: Applied Energy. RePEc:eee:appene:v:341:y:2023:i:c:s030626192300418x.

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2023Adaptive control of V2Gs in islanded microgrids incorporating EV owner expectations. (2023). Mahmoudian, Ali ; Taghizadeh, Foad ; Sanjari, Mohammad ; Garmabdari, Rasoul ; Bai, Feifei ; Mousavizade, Mirsaeed ; Lu, Junwei. In: Applied Energy. RePEc:eee:appene:v:341:y:2023:i:c:s0306261923004828.

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2022Intraday Trading of Precious Metals Futures Using Algorithmic Systems. (2022). Gil, Cohen. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:154:y:2022:i:c:s0960077921010304.

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2022A time power-based grey model with conformable fractional derivative and its applications. (2022). Goh, Mark ; Xie, Wanli ; Liu, Chong ; Zeng, Liang ; Wu, Wen-Ze. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:155:y:2022:i:c:s0960077921010110.

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2022Prediction of crude oil prices in COVID-19 outbreak using real data. (2022). Kaymak, Yiit. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922002004.

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2022Forecasting of a complex phenomenon using stochastic data-based techniques under non-conventional schemes: The SARS-CoV-2 virus spread case. (2022). Samaniego, Esteban P ; Ochoa-Sanchez, Ana ; Mendoza, Daniel E. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:158:y:2022:i:c:s0960077922003071.

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2022A flexible grey Fourier model based on integral matching for forecasting seasonal PM2.5 time series. (2022). Yang, LU ; Xie, Naiming ; Wang, Xiaolei. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:162:y:2022:i:c:s0960077922006270.

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2023An ensemble neural network approach to forecast Dengue outbreak based on climatic condition. (2023). Ghosh, Indrajit ; Nadim, Sk Shahid ; Chakraborty, Tanujit ; Panja, Madhurima ; Liu, Nan ; Kumar, Uttam. In: Chaos, Solitons & Fractals. RePEc:eee:chsofr:v:167:y:2023:i:c:s0960077923000255.

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2022Bayesian spatio-temporal models for stream networks. (2022). Mengersen, Kerrie ; Isaak, Daniel J ; McGree, James ; Peterson, Erin E ; Ver, Jay M ; Santos-Fernandez, Edgar . In: Computational Statistics & Data Analysis. RePEc:eee:csdana:v:170:y:2022:i:c:s0167947322000263.

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2023Assessing the World Bank’s growth forecasts. (2023). Tsuchiya, Yoichi. In: Economic Analysis and Policy. RePEc:eee:ecanpo:v:77:y:2023:i:c:p:64-84.

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2022Forecasting solar stock prices using tree-based machine learning classification: How important are silver prices?. (2022). Sadorsky, Perry. In: The North American Journal of Economics and Finance. RePEc:eee:ecofin:v:61:y:2022:i:c:s1062940822000572.

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2023Economic and commercial analysis of reusing dam reservoir sediments. (2023). Schleiss, Anton J ; Heydariyeh, Seyyed Abdollah ; Alroaia, Younos Vakil ; Nikafkar, Nasrin. In: Ecological Economics. RePEc:eee:ecolec:v:204:y:2023:i:pb:s0921800922003299.

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2022A northeast United States Atlantis marine ecosystem model with ocean reanalysis and ocean color forcing. (2022). Stock, Charles A ; Caracappa, Joseph C ; Gaichas, Sarah ; Beet, Andrew ; Morse, Ryan E ; Saba, Vincent S ; Large, Scott I ; Gamble, Robert J. In: Ecological Modelling. RePEc:eee:ecomod:v:471:y:2022:i:c:s030438002200148x.

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2022From zero to hero: Realized partial (co)variances. (2022). Quaedvlieg, Rogier ; Patton, Andrew J ; Medeiros, Marcelo C ; Bollerslev, Tim. In: Journal of Econometrics. RePEc:eee:econom:v:231:y:2022:i:2:p:348-360.

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2022A nonparametric copula approach to conditional Value-at-Risk. (2022). Dunn, Richard ; Geenens, Gery. In: Econometrics and Statistics. RePEc:eee:ecosta:v:21:y:2022:i:c:p:19-37.

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2022Forecast adjustments during post-promotional periods. (2022). de Baets, Shari ; Perera, Niles H ; Hewage, Harsha Chamara. In: European Journal of Operational Research. RePEc:eee:ejores:v:300:y:2022:i:2:p:461-472.

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2022Forecast with forecasts: Diversity matters. (2022). Li, Feng ; Petropoulos, Fotios ; Cao, Wei ; Kang, Yanfei. In: European Journal of Operational Research. RePEc:eee:ejores:v:301:y:2022:i:1:p:180-190.

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More than 100 citations found, this list is not complete...

Rob J Hyndman is editor of

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Monash Econometrics and Business Statistics Working Papers

Works by Rob J Hyndman:

YearTitleTypeCited
2011Coherent Mortality Forecasting The Product-ratio Method with Functional Time Series Models In: Working Papers.
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2011Coherent mortality forecasting: the product-ratio method with functional time series models.(2011) In: Monash Econometrics and Business Statistics Working Papers.
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2013Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models.(2013) In: Demography.
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2020Modern Strategies for Time Series Regression In: International Statistical Review.
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1997Some Properties and Generalizations of Non?negative Bayesian Time Series Models In: Journal of the Royal Statistical Society Series B.
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1993YULE?WALKER ESTIMATES FOR CONTINUOUS?TIME AUTOREGRESSIVE MODELS In: Journal of Time Series Analysis.
[Full Text][Citation analysis]		article2
2022Seasonal functional autoregressive models In: Journal of Time Series Analysis.
[Full Text][Citation analysis]		article1
2019Seasonal Functional Autoregressive Models.(2019) In: Monash Econometrics and Business Statistics Working Papers.
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2006Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions In: Demographic Research.
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2011Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods In: Demographic Research.
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2004Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC In: Econometric Society 2004 Australasian Meetings.
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2004Bandwidth Selection for Multivariate Kernel Density Estimation Using MCMC.(2004) In: Monash Econometrics and Business Statistics Working Papers.
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2018A note on the validity of cross-validation for evaluating autoregressive time series prediction In: Computational Statistics & Data Analysis.
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1998Smoothing non-Gaussian time series with autoregressive structure In: Computational Statistics & Data Analysis.
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2001Bandwidth selection for kernel conditional density estimation In: Computational Statistics & Data Analysis.
[Full Text][Citation analysis]		article59
1998Bandwidth Selection for Kernel Conditional Density Estimation..(1998) In: Monash Econometrics and Business Statistics Working Papers.
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2006A Bayesian approach to bandwidth selection for multivariate kernel density estimation In: Computational Statistics & Data Analysis.
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2007Robust forecasting of mortality and fertility rates: A functional data approach In: Computational Statistics & Data Analysis.
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2005Robust forecasting of mortality and fertility rates: a functional data approach.(2005) In: Monash Econometrics and Business Statistics Working Papers.
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2007Half-life estimation based on the bias-corrected bootstrap: A highest density region approach In: Computational Statistics & Data Analysis.
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2006Half-Life Estimation based on the Bias-Corrected Bootstrap: A Highest Density Region Approach.(2006) In: Monash Econometrics and Business Statistics Working Papers.
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2011Improved interval estimation of long run response from a dynamic linear model: A highest density region approach In: Computational Statistics & Data Analysis.
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2010Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach.(2010) In: Working Papers.
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2010Improved Interval Estimation of Long Run Response from a Dynamic Linear Model: A Highest Density Region Approach.(2010) In: Working Papers.
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2011Optimal combination forecasts for hierarchical time series In: Computational Statistics & Data Analysis.
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2007Optimal combination forecasts for hierarchical time series.(2007) In: Monash Econometrics and Business Statistics Working Papers.
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2016Fast computation of reconciled forecasts for hierarchical and grouped time series In: Computational Statistics & Data Analysis.
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2014Fast computation of reconciled forecasts for hierarchical and grouped time series.(2014) In: Monash Econometrics and Business Statistics Working Papers.
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2009A multivariate innovations state space Beveridge-Nelson decomposition In: Economic Modelling.
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2004Exponential smoothing models: Means and variances for lead-time demand In: European Journal of Operational Research.
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2008Forecasting time series with multiple seasonal patterns In: European Journal of Operational Research.
[Full Text][Citation analysis]		article44
2017Forecasting with temporal hierarchies In: European Journal of Operational Research.
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2015Forecasting with Temporal Hierarchies.(2015) In: Monash Econometrics and Business Statistics Working Papers.
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2015Forecasting with Temporal Hierarchies.(2015) In: MPRA Paper.
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2018Exploring the sources of uncertainty: Why does bagging for time series forecasting work? In: European Journal of Operational Research.
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2021Forecasting Swiss exports using Bayesian forecast reconciliation In: European Journal of Operational Research.
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2019Forecasting Swiss Exports Using Bayesian Forecast Reconciliation.(2019) In: Monash Econometrics and Business Statistics Working Papers.
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2023Probabilistic forecast reconciliation: Properties, evaluation and score optimisation In: European Journal of Operational Research.
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2020Probabilistic Forecast Reconciliation: Properties, Evaluation and Score Optimisation.(2020) In: Monash Econometrics and Business Statistics Working Papers.
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2011The price elasticity of electricity demand in South Australia In: Energy Policy.
[Full Text][Citation analysis]		article89
2010The price elasticity of electricity demand in South Australia.(2010) In: Monash Econometrics and Business Statistics Working Papers.
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2021Assessing mortality inequality in the U.S.: What can be said about the future? In: Insurance: Mathematics and Economics.
[Full Text][Citation analysis]		article2
2002A state space framework for automatic forecasting using exponential smoothing methods In: International Journal of Forecasting.
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2000A State Space Framework for Automatic Forecasting Using Exponential Smoothing Methods..(2000) In: Monash Econometrics and Business Statistics Working Papers.
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2003Unmasking the Theta method In: International Journal of Forecasting.
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2001Unmasking the Theta Method..(2001) In: Monash Econometrics and Business Statistics Working Papers.
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2004The interaction between trend and seasonality In: International Journal of Forecasting.
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2005Editorial In: International Journal of Forecasting.
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2006Twenty-five years of forecasting In: International Journal of Forecasting.
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200625 years of time series forecasting In: International Journal of Forecasting.
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2006Another look at measures of forecast accuracy In: International Journal of Forecasting.
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2005Another Look at Measures of Forecast Accuracy.(2005) In: Monash Econometrics and Business Statistics Working Papers.
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2008Stochastic population forecasts using functional data models for mortality, fertility and migration In: International Journal of Forecasting.
[Full Text][Citation analysis]		article44
2006Stochastic population forecasts using functional data models for mortality, fertility and migration.(2006) In: Monash Econometrics and Business Statistics Working Papers.
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2008Call for Papers: Special issue of the International Journal of Forecasting on tourism forecasting In: International Journal of Forecasting.
[Full Text][Citation analysis]		article0
2009A change of editors In: International Journal of Forecasting.
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2009Hierarchical forecasts for Australian domestic tourism In: International Journal of Forecasting.
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2007Hierarchical forecasts for Australian domestic tourism.(2007) In: Monash Econometrics and Business Statistics Working Papers.
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2009Monitoring processes with changing variances In: International Journal of Forecasting.
[Full Text][Citation analysis]		article1
2008Monitoring Processes with Changing Variances.(2008) In: Monash Econometrics and Business Statistics Working Papers.
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2010Changing of the guard In: International Journal of Forecasting.
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2010Encouraging replication and reproducible research In: International Journal of Forecasting.
[Full Text][Citation analysis]		article1
2011The tourism forecasting competition In: International Journal of Forecasting.
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2011The tourism forecasting competition.(2011) In: International Journal of Forecasting.
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2009The tourism forecasting competition.(2009) In: Monash Econometrics and Business Statistics Working Papers.
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This paper has another version. Agregated cites: 82		paper
2011The value of feedback in forecasting competitions In: International Journal of Forecasting.
[Full Text][Citation analysis]		article8
2011The value of feedback in forecasting competitions.(2011) In: International Journal of Forecasting.
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2011The value of feedback in forecasting competitions.(2011) In: Monash Econometrics and Business Statistics Working Papers.
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2011Tourism forecasting: An introduction In: International Journal of Forecasting.
[Full Text][Citation analysis]		article7
2014A gradient boosting approach to the Kaggle load forecasting competition In: International Journal of Forecasting.
[Full Text][Citation analysis]		article52
2016Bagging exponential smoothing methods using STL decomposition and Box–Cox transformation In: International Journal of Forecasting.
[Full Text][Citation analysis]		article46
2014Bagging Exponential Smoothing Methods using STL Decomposition and Box-Cox Transformation.(2014) In: Monash Econometrics and Business Statistics Working Papers.
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2016Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond In: International Journal of Forecasting.
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2017Visualising forecasting algorithm performance using time series instance spaces In: International Journal of Forecasting.
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2016Visualising forecasting Algorithm Performance using Time Series Instance Spaces.(2016) In: Monash Econometrics and Business Statistics Working Papers.
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2018Crude oil price forecasting based on internet concern using an extreme learning machine In: International Journal of Forecasting.
[Full Text][Citation analysis]		article36
2019Macroeconomic forecasting for Australia using a large number of predictors In: International Journal of Forecasting.
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2017Macroeconomic forecasting for Australia using a large number of predictors.(2017) In: Monash Econometrics and Business Statistics Working Papers.
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2020Forecasting in social settings: The state of the art In: International Journal of Forecasting.
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2020A brief history of forecasting competitions In: International Journal of Forecasting.
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2019A Brief History of Forecasting Competitions.(2019) In: Monash Econometrics and Business Statistics Working Papers.
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2020FFORMA: Feature-based forecast model averaging In: International Journal of Forecasting.
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2018FFORMA: Feature-based forecast model averaging.(2018) In: Monash Econometrics and Business Statistics Working Papers.
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2021Forecast reconciliation: A geometric view with new insights on bias correction In: International Journal of Forecasting.
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2019Forecast Reconciliation: A geometric View with New Insights on Bias Correction.(2019) In: Monash Econometrics and Business Statistics Working Papers.
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2020Forecast Reconciliation: A geometric View with New Insights on Bias Correction.(2020) In: Monash Econometrics and Business Statistics Working Papers.
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2021Principles and algorithms for forecasting groups of time series: Locality and globality In: International Journal of Forecasting.
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2020Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality.(2020) In: Monash Econometrics and Business Statistics Working Papers.
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2022Forecasting for social good In: International Journal of Forecasting.
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2020Forecasting for Social Good.(2020) In: Monash Econometrics and Business Statistics Working Papers.
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1992On continuous-time threshold autoregression In: International Journal of Forecasting.
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2011Nonparametric time series forecasting with dynamic updating In: Mathematics and Computers in Simulation (MATCOM).
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2009Nonparametric time series forecasting with dynamic updating.(2009) In: Monash Econometrics and Business Statistics Working Papers.
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2003Improved methods for bandwidth selection when estimating ROC curves In: Statistics & Probability Letters.
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2002An Improved Method for Bandwidth Selection when Estimating ROC Curves.(2002) In: Monash Econometrics and Business Statistics Working Papers.
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2017The Australian Macro Database: An online resource for macroeconomic research in Australia In: CAMA Working Papers.
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2017The Australian Macro Database: An online resource for macroeconomic research in Australia.(2017) In: Monash Econometrics and Business Statistics Working Papers.
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2002Nonparametric estimation and symmetry tests for conditional density functions In: LSE Research Online Documents on Economics.
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1998Nonparametric Estimation and Symmetry Tests for Conditional Density Functions..(1998) In: Monash Econometrics and Business Statistics Working Papers.
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2006Another Look at Forecast Accuracy Metrics for Intermittent Demand In: Foresight: The International Journal of Applied Forecasting.
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2007Minimum Sample Size requirements for Seasonal Forecasting Models In: Foresight: The International Journal of Applied Forecasting.
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2010Free Open-Source Forecasting Using R In: Foresight: The International Journal of Applied Forecasting.
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2014Optimally Reconciling Forecasts in a Hierarchy In: Foresight: The International Journal of Applied Forecasting.
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2008Exponential smoothing and non-negative data In: Working Papers.
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2002Using R to teach econometrics In: Journal of Applied Econometrics.
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2001Using R to Teach Econometrics..(2001) In: Monash Econometrics and Business Statistics Working Papers.
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2005Prediction intervals for exponential smoothing using two new classes of state space models In: Journal of Forecasting.
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2005Stochastic models underlying Crostons method for intermittent demand forecasting In: Journal of Forecasting.
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2003Stochastic models underlying Crostons method for intermittent demand forecasting.(2003) In: Monash Econometrics and Business Statistics Working Papers.
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2008Automatic Time Series Forecasting: The forecast Package for R In: Journal of Statistical Software.
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2007Automatic time series forecasting: the forecast package for R..(2007) In: Monash Econometrics and Business Statistics Working Papers.
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1998Residual Diagnostic Plots for Checking for model Mis-Specification in Time Series Regression. In: Monash Econometrics and Business Statistics Working Papers.
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1999Generalized Additive Modelling of Mixed Distribution Markov Models with Application to Melbournes Rainfall. In: Monash Econometrics and Business Statistics Working Papers.
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2000Mixed Model-Based Hazard Estimation. In: Monash Econometrics and Business Statistics Working Papers.
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2001Prediction Intervals for Exponential Smoothing State Space Models. In: Monash Econometrics and Business Statistics Working Papers.
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2001Statistical Methodological Issues in Studies of Air Pollution and Respiratory Disease. In: Monash Econometrics and Business Statistics Working Papers.
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2002Local Linear Forecasts Using Cubic Smoothing Splines In: Monash Econometrics and Business Statistics Working Papers.
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2002Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand In: Monash Econometrics and Business Statistics Working Papers.
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2003Non Parametric Confidence Intervals for Receiver Operating Characteristic Curves In: Monash Econometrics and Business Statistics Working Papers.
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2003Empirical Information Criteria for Time Series Forecasting Model Selection In: Monash Econometrics and Business Statistics Working Papers.
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2003Invertibility Conditions for Exponential Smoothing Models In: Monash Econometrics and Business Statistics Working Papers.
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2005Forecasting Time-Series with Correlated Seasonality In: Monash Econometrics and Business Statistics Working Papers.
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2005Rating Forecasts for Television Programs In: Monash Econometrics and Business Statistics Working Papers.
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200525 Years of IIF Time Series Forecasting: A Selective Review In: Monash Econometrics and Business Statistics Working Papers.
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200525 Years of IIF Time Series Forecasting: A Selective Review.(2005) In: Tinbergen Institute Discussion Papers.
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2005Forecasting age-specific breast cancer mortality using functional data models In: Monash Econometrics and Business Statistics Working Papers.
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2005Time Series Forecasting: The Case for the Single Source of Error State Space In: Monash Econometrics and Business Statistics Working Papers.
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2006Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions In: Monash Econometrics and Business Statistics Working Papers.
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2006Modelling and forecasting Australian domestic tourism In: Monash Econometrics and Business Statistics Working Papers.
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2006Some Nonlinear Exponential Smoothing Models are Unstable In: Monash Econometrics and Business Statistics Working Papers.
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2006Local Linear Multivariate Regression with Variable Bandwidth in the Presence of Heteroscedasticity In: Monash Econometrics and Business Statistics Working Papers.
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2007Non-linear exponential smoothing and positive data In: Monash Econometrics and Business Statistics Working Papers.
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2007The vector innovation structural time series framework: a simple approach to multivariate forecasting In: Monash Econometrics and Business Statistics Working Papers.
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2007A state space model for exponential smoothing with group seasonality In: Monash Econometrics and Business Statistics Working Papers.
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2008Density forecasting for long-term peak electricity demand In: Monash Econometrics and Business Statistics Working Papers.
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2008Rainbow plots, Bagplots and Boxplots for Functional Data In: Monash Econometrics and Business Statistics Working Papers.
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2009Forecasting time series with complex seasonal patterns using exponential smoothing In: Monash Econometrics and Business Statistics Working Papers.
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2010Short-term load forecasting based on a semi-parametric additive model In: Monash Econometrics and Business Statistics Working Papers.
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2010A comparison of ten principal component methods for forecasting mortality rates In: Monash Econometrics and Business Statistics Working Papers.
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2010Forecasting age-related changes in breast cancer mortality among white and black US women: A functional approach In: Monash Econometrics and Business Statistics Working Papers.
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2012Recursive and direct multi-step forecasting: the best of both worlds In: Monash Econometrics and Business Statistics Working Papers.
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2013Two-dimensional smoothing of mortality rates In: Monash Econometrics and Business Statistics Working Papers.
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2014Efficient Identification of the Pareto Optimal Set In: Monash Econometrics and Business Statistics Working Papers.
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2014Boosting multi-step autoregressive forecasts In: Monash Econometrics and Business Statistics Working Papers.
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2014Low-dimensional decomposition, smoothing and forecasting of sparse functional data In: Monash Econometrics and Business Statistics Working Papers.
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2015A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction In: Monash Econometrics and Business Statistics Working Papers.
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2015Probabilistic time series forecasting with boosted additive models: an application to smart meter data In: Monash Econometrics and Business Statistics Working Papers.
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2015STR: A Seasonal-Trend Decomposition Procedure Based on Regression In: Monash Econometrics and Business Statistics Working Papers.
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2015Forecasting hierarchical and grouped time series through trace minimization In: Monash Econometrics and Business Statistics Working Papers.
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2016Long-term forecasts of age-specific participation rates with functional data models In: Monash Econometrics and Business Statistics Working Papers.
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2016Grouped functional time series forecasting: An application to age-specific mortality rates In: Monash Econometrics and Business Statistics Working Papers.
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2016Bayesian Rank Selection in Multivariate Regression In: Monash Econometrics and Business Statistics Working Papers.
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2017Optimal forecast reconciliation for hierarchical and grouped time series through trace minimization In: Monash Econometrics and Business Statistics Working Papers.
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2019Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization.(2019) In: Journal of the American Statistical Association.
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2017Coherent Probabilistic Forecasts for Hierarchical Time Series In: Monash Econometrics and Business Statistics Working Papers.
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2018Probabilisitic forecasts in hierarchical time series In: Monash Econometrics and Business Statistics Working Papers.
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2018Efficient generation of time series with diverse and controllable characteristics In: Monash Econometrics and Business Statistics Working Papers.
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2018On normalization and algorithm selection for unsupervised outlier detection In: Monash Econometrics and Business Statistics Working Papers.
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2018Anomaly detection in streaming nonstationary temporal data In: Monash Econometrics and Business Statistics Working Papers.
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