Prof Rob Hyndman - Researcher Profile

Rob J Hyndman

Address

Department of Econometrics and Business Statistics
Monash University, Clayton

Contact Details

Tel: +61 3 990 55141

Email: Rob.Hyndman@monash.edu


Biography

Rob J Hyndman is a Professor of Statistics in the Department of Econometrics and Business Statistics.

His academic qualifications include a Bachelor of Science (Honours) and a PhD from the University of Melbourne. He is an accredited statistician with the Statistical Society of Australia.

Rob has researched and consulted with a wide range of business, industry and government clients. His most recent work includes demand forecasting for the electricity industry, estimating life expectancy for the Australian indigenous population, and forecasting the national health budget.

He has held academic positions at Monash University, the University of Melbourne, Australian National University and Colorado State University. He is currently a director of the International Institute of Forecasters, editor-in-chief of International Journal of Forecasting and director of the Business and Economic Forecasting Unit in the Department of Econometrics and Business Statistics at Monash University.

He is an elected member of the International Statistical Institute and a member of the International Institute of Forecasters, International Association for Statistical Computing, Institute of Mathematical Statistics, American Statistical Association and the Statistical Society of Australia.

Rob has received several awards for his research including the 2007 Moran Medal from the Australian Academy of Science. He has also been a recipient of the Dean’s Award for excellence in innovation and external collaboration (2010), the HP Innovation Research Award (2010), the Vice Chancellor's Award for Postgraduate Supervision (2008) and the Dean’s award for excellence in research (2008).

Rob’s research interests include forecasting, time series analysis, statistical computing, and computational demography. He has also supervised more than 25 PhD and Masters students, with current projects including forecasting functional data, non-Gaussian time series models, hierarchical forecasting, nonparametric smoothing of age-period-cohort structures.

Keywords

forecasting, demography, computational statistics, time series

Qualifications

DOCTORATE IN PHILOSOPHY
Institution: University of Melbourne
Year awarded: 1993
SCIENCE
Institution: University of Melbourne
Year awarded: 1989

Publications

Books

Hyndman, R.J., Koehler, A.B., Ord, J., Snyder, R.D., 2008, Forecasting with Exponential Smoothing: The State Space Approach, Springer, Berlin Germany.

Hyndman, R.J., Grunwald, G.K., 1999, Generalized additive modelling of mixed distribution Markov models with application to Melbourne's rainfall, Monash University, Melbourne Vic Australia.

Hyndman, R.J. (ed), 1998, Australian and New Zealand Journal of Statistics, Australian Statistical Publishing Association, Canberra ACT Australia.

Bashtannyk, D.M., Hyndman, R.J., 1998, Bandwidth selection for kernal conditional density estimation, Monash University, Melbourne Vic Australia.

Hyndman, R.J., Yao, Q., 1998, Nonparametric estimation and symmetry tests for conditional density functions, Monash University, Melbourne Vic Australia.

Fraccaro, R., Hyndman, R.J., Veevers, A., 1998, Residual diagnostic plots for checking for model mis-specification in time series regression, Monash University, Melbourne Vic Australia.

Makridakis, S., Wheelwright, S., Hyndman, R.J., 1997, Forecasting: Methods and Applications, 3rd Ed, John Wiley & Sons, New York NY USA.

Makridakis, S., Wheelwright, S., Hyndman, R.J., 1997, Instructor's Manual to Forecasting: methods and applications, John Wiley & Sons, New York NY USA.

Book Chapters

Hyndman, R.J., Shang, H.L., 2008, Bagplots, boxplots and outlier detection for functional data, in Functional and Operatorial Statistics, eds Sophie Dabo-Niang and Frederic Ferraty, Physica-Verlag, Heidelberg Germany, pp. 201-207.

Journal Articles

Erbas, B., Dharmage, S.C., O'Sullivan, M., Akram, M., Newbigin, E.J., Taylor, P.E., Vicendese, D., Hyndman, R.J., Bardin, P.G., Tang, M.L., Abramson, M.J., 2012, A case-crossover design to examine the role of eeroallergens and respiratory viruses on childhood asthma exacerbations requiring hospitalization: the Mapcah study, Journal of Biometrics & Biostatistics [E], vol S7, Omics Publishing Group, United States, pp. 1-6.

Erbas, B., Ullah, M.S., Hyndman, R.J., Scollo, M., Abramson, M.J., 2012, Forecasts of COPD mortality in Australia: 2006-2025, BMC Medical Research Methodology [P], vol 12, BioMed Central Ltd, London UK, pp. 1-9.

Fan, S., Hyndman, R.J., 2012, Short-term load forecasting based on a semi-parametric additive model, IEEE Transactions on Power Systems [P], vol 27, issue 1, Institute of Electrical and Electronics Engineers, Piscataway USA, pp. 134-141.

De Livera, A., Hyndman, R., Snyder, R., 2011, Forecasting time series with complex seasonal patterns using exponential smoothing, Journal Of The American Statistical Association [P], vol 106, issue 496, American Statistical Association, Baltimore MD USA, pp. 1513-1527.

Kim, J., Fraser, I., Hyndman, R., 2011, Improved interval estimation of long run response from a dynamic linear model: A highest density region approach, Computational Statistics and Data Analysis [P], vol 55, issue 8, Elsevier BV, Amsterdam Netherlands, pp. 2477-2489.

Pearce, J., Beringer, J., Nicholls, N., Hyndman, R., Uotila, J., Tapper, N., 2011, Investigating the influence of synoptic-scale meteorology on air quality using self-organizing maps and generalized additive modelling, Atmospheric Environment [P], vol 45, issue 1, Pergamon, UK, pp. 128-136.

Carta, D., Villanova, L., Costacurta, S., Patelli, A., Poli, I., Vezzu, S., Scopece, P., Lisi, F., Smith-Miles, K., Hyndman, R., Hill, A., Falcaro, P., 2011, Method for optimizing coating properties based on an evolutionary algorithm approach, Analytical Chemistry [P], vol 83, issue 16, American Chemical Society, US, pp. 6373-6380.

Shang, H., Hyndman, R., 2011, Nonparametric time series forecasting with dynamic updating, Mathematics and Computers in Simulation [P], vol 81, issue 7, Elsevier BV, Amsterdam Netherlands, pp. 1310-1324.

Hyndman, R., Ahmed, R., Athanasopoulos, G., Shang, H., 2011, Optimal combination forecasts for hierarchical time series, Computational Statistics and Data Analysis [P], vol 55, issue 9, Elsevier BV, Amsterdam Netherlands, pp. 2579-2589.

Shang, H., Booth, H., Hyndman, R., 2011, Point and interval forecasts of mortality rates and life expectancy: A comparison of ten principal component methods, Demographic Research [P], vol 25, Max-Planck-Institut fuer Demografische Forschung, Rostock Germany, pp. 173-214.

Pearce, J., Beringer, J., Nicholls, N., Hyndman, R., Tapper, N., 2011, Quantifying the influence of local meteorology on air quality using generalized additive models, Atmospheric Environment [P], vol 45, issue 6, Pergamon, UK, pp. 1328-1336.

Fan, S., Hyndman, R., 2011, The price elasticity of electricity demand in South Australia, Energy Policy [P], vol 39, issue 6, Pergamon, Oxford UK, pp. 3709-3719.

Athanasopoulos, G., Hyndman, R., Song, H., Wu, D., 2011, The tourism forecasting competition, International Journal of Forecasting [P], vol 27, issue 3, Elsevier BV, Amsterdam Netherlands, pp. 822-844.

Athanasopoulos, G., Hyndman, R., 2011, The value of feedback in forecasting competitions, International Journal of Forecasting [P], vol 27, issue 3, Elsevier BV, Amsterdam Netherlands, pp. 845-849.

Hyndman, R.J., Fan, S., 2010, Density forecasting for long-term peak electricity demand, IEEE Transactions on Power Systems [P], vol 25, issue 2, IEEE, USA, pp. 1142-1153.

Verbesselt, J., Hyndman, R.J., Newnham, G., Culvenor, D., 2010, Detecting trend and seasonal changes in satellite image time series, Remote Sensing of Environment [P], vol 114, issue 1, Elsevier Inc, USA, pp. 106-115.

Yasmeen, F., Hyndman, R., Erbas, B., 2010, Forecasting age-related changes in breast cancer mortality among white and black US women: A functional data approach, Cancer Epidemiology [P], vol 34, issue 5, Elsevier Inc, USA, pp. 542-549.

Verbesselt, J., Hyndman, R., Zeileis, A., Culvenor, D., 2010, Phenological change detection while accounting for abrupt and gradual trends in satellite image time series, Remote Sensing of Environment [P], vol 114, issue 12, Elsevier Inc, USA, pp. 2970-2980.

Hyndman, R.J., Shang, H.L., 2010, Rainbow plots, bagplots, and boxplots for functional data, Journal Of Computational And Graphical Statistics [P], vol 19, issue 1, American Statistical Association, USA, pp. 29-45.

de Silva, A., Hyndman, R., Snyder, R., 2010, The vector innovations structural time series framework: A simple approach to multivariate forecasting, Statistical Modelling [P], vol 10, issue 4, Sage Publications India Pvt Ltd, India, pp. 353-374.

Erbas, B., Akram, M., Gertig, D., English, D.R., Hopper, J.L., Kavanagh, A.M., Hyndman, R.J., 2010, Using functional data analysis models to estimate future time trends in age-specific breast cancer mortality for the United States and England-Wales, Journal Of Epidemiology [P], vol 20, issue 2, Japan Epidemiological Association, Japan, pp. 159-165.

de Silva, A., Hyndman, R.J., Snyder, R.D., 2009, A multivariate innovations state space Beveridge-Nelson decomposition, Economic Modelling [P], vol 26, issue 5, Elsevier BV, North-Holland, Netherlands, pp. 1067-1074.

Akram, M., Hyndman, R.J., Ord, J.K., 2009, Exponential smoothing and non-negative data, Australian & New Zealand Journal Of Statistics [P], vol 51, issue 4, Wiley-Blackwell Publishing Asia, Richmond Vic Australia, pp. 415-432.

Hyndman, R.J., Shang, H.L., 2009, Forecasting functional time series, Journal of the Korean Statistical Society [P], vol 38, issue 3, Elsevier BV, Netherlands, pp. 199-211.

Athanasopoulos, G., Ahmed, R.A., Hyndman, R.J., 2009, Hierarchical forecasts for Australian domestic tourism, International Journal of Forecasting [P], vol 25, issue 1, Elsevier BV, Netherlands, pp. 146-166.

Ord, J., Koehler, A.B., Snyder, R.D., Hyndman, R.J., 2009, Monitoring processes with changing variances, International Journal of Forecasting [P], vol 25, issue 3, Elsevier BV, The Netherlands, pp. 518-525.

Hyndman, R.J., Shang, H.L., 2009, Rejoinder: Forecasting functional time series, Journal of the Korean Statistical Society [P], vol 38, issue 3, Elsevier BV, Netherlands, pp. 219-221.

Wang, X., Smith-Miles, K., Hyndman, R.J., 2009, Rule induction for forecasting method selection: Meta-learning the characteristics of univariate time series, Neurocomputing, vol 72, Elsevier BV, Netherlands, pp. 2581-2594.

Hyndman, R.J., Khandakar, Y., 2008, Automatic time series forecasting: The forecast Package for R, Journal of Statistical Software, vol 27, issue 3, University of California, Los Angeles, Department of Statistics, USA, pp. 1-22.

Gould, P.G., Koehler, A.B., Ord, J.K., Snyder, R.D., Hyndman, R.J., Vahid-Araghi, F., 2008, Forecasting time series with multiple seasonal patterns, European Journal of Operational Research, vol 191, issue 1, Elsevier BV, North-Holland, Netherlands, pp. 205-220.

Magnano, L., Boland, J.W., Hyndman, R.J., 2008, Generation of synthetic sequences of half-hourly temperature, Environmetrics, vol 19, issue 8, John Wiley & Sons Ltd, UK, pp. 818-835.

Athanasopoulos, G., Hyndman, R.J., 2008, Modelling and forecasting Australian domestic tourism, Tourism Management, vol 29, issue 1, Pergamon, UK, pp. 19-31.

Hyndman, R.J., Booth, H., 2008, Stochastic population forecasts using functional data models for mortality, fertility and migration, International Journal of Forecasting, vol 24, issue 3, Elsevier BV, North-Holland, Netherlands, pp. 323-342.

Hyndman, R.J., Akram, M., Archibald, B.C., 2008, The admissible parameter space for exponential smoothing models, Annals of the Institute of Statistical Mathematics, vol 60, issue 2, Springer, Germany, pp. 407-426.

Erbas, B., Chang, J.J., Dharmage, S., Ong, E.K., Hyndman, R.J., Newbigin, E.J., Abramson, M.J., 2007, Do levels of airborne grass pollen influence asthma hospital admissions?, Clinical and Experimental Allergy, vol 37, issue 11, Wiley-Blackwell Publishing, UK, pp. 1641-1647.

Erbas, B., Hyndman, R.J., Gertig, D., 2007, Forecasting age-specific breast cancer mortality using functional data models, Statistics in Medicine, vol 26, issue 2, John Wiley & Sons Ltd, UK, pp. 458-470.

Kim, J., Silvapulle, P., Hyndman, R.J., 2007, Half-life estimation based on the bias-corrected bootstrap: A highest density region approach, Computational Statistics & Data Analysis, vol 51, issue 7, Elsevier BV, North-Holland, Netherlands, pp. 3418-3432.

Horn, F.E., Mandryk, J.A., Mackson, J.M., Wutzke, S.E., Weekes, L.M., Hyndman, R.J., 2007, Measurement of changes in antihypertensive drug utilisation following primary care educational interventions, Pharmacoepidemiology and Drug Safety, vol 16, issue 3, John Wiley & Sons Ltd, UK, pp. 297-308.

Hyndman, R.J., Kostenko, A., 2007, Minimum sample size requirements for seasonal forecasting models, Foresight, vol Spring, issue 6, International Institute of Forecasters, USA, pp. 12-15.

Hyndman, R.J., Ullah, M.S., 2007, Robust forecasting of mortality and fertility rates: A functional data approach, Computational Statistics & Data Analysis, vol 51, issue 10, Elsevier BV, North-Holland, Netherlands, pp. 4942-4956.

De Gooijer, J.G., Hyndman, R.J., 2006, 25 years of time series forecasting, International Journal of Forecasting, vol 22, issue 3, Elsevier, The Netherlands, pp. 443-473.

Zhang, X., King, M.L., Hyndman, R.J., 2006, A Bayesian approach to bandwidth selection for multivariate kernel density estimation, Computational Statistics & Data Analysis, vol 50, issue 11, Elsevier, The Netherlands, pp. 3009-3031.

Kostenko, A.V., Hyndman, R.J., 2006, A note on the categorization of demand patterns, Journal of the Operational Research Society, vol 57, issue 10, Palgrave Macmillan Ltd, UK, pp. 1256-1257.

Hyndman, R.J., 2006, Another look at forecast-accuracy metrics for intermittent demand, Foresight: The International Journal of Applied Forecasting, vol 4, issue 4, International Institute of Forecasters, Medford USA, pp. 43-46.

Hyndman, R.J., Koehler, A.B., 2006, Another look at measures of forecast accuracy, International Journal of Forecasting, vol 22, issue 4, Elsevier, The Netherlands, pp. 679-688.

Wang, X.C., Smith, K.A., Hyndman, R.J., 2006, Characteristic-based clustering for time series data, The Journal of Data Mining and Knowledge Discovery, vol 13, issue 3, Springer New York LLC, New York USA, pp. 335-364.

Booth, H., Hyndman, R.J., Tickle, L., de Jong, P., 2006, Lee-Carter mortality forecasting: A multi-country comparison of variants and extensions, Demographic Research, vol 15, issue 9, Max-Planck-Institut fuer Demografische Forschung, Germany, pp. 289-310.

Mandryk, J.A., Mackson, J.M., Horn, F.E., Wutzke, S.E., Badcock, C., Hyndman, R.J., Weekes, L.M., 2006, Measuring change in prescription drug utilization in Australia, Pharmacoepidemiology and Drug Safety, vol 15, issue 7, John Wiley & Sons Ltd, UK, pp. 477-484.

Meyer, D., Hyndman, R.J., 2006, The accuracy of television network rating forecasts: the effects of data aggregation and alternative models, Model Assisted Statistics and Applications, vol 1, issue 3, IOS Press, The Netherlands, pp. 145-153.

Hyndman, R.J., Ord, J.K., 2006, Twenty-five years of forecasting, International Journal of Forecasting, vol 22, issue 3, Elsevier BV, North-Holland, Netherlands, pp. 413-414.

Billah, M.B., Hyndman, R.J., Koehler, A.B., 2005, Empirical information criteria for time series forecasting model selection, Journal of Statistical Computation and Simulation, vol 75, issue 10, Gordon & Breach, UK, pp. 831-840.

Hyndman, R.J., King, M.L., Pitrun, I., Billah, M.B., 2005, Local linear forecasts using cubic smoothing splines, Australian & New Zealand Journal of Statistics, vol 47, issue 1, Blackwell Science Ltd, Australia, pp. 87-99.

Hyndman, R.J., Koehler, A.B., Ord, J.K., Snyder, R.D., 2005, Prediction intervals for exponential smoothing using two new classes of state space models, Journal of Forecasting, vol 24, issue 1, John Wiley & Sons Ltd, UK, pp. 17-37.

Erbas, B., Hyndman, R.J., 2005, Sensitivity of the estimated air pollution-respiratory admissions relationship to statistical model choice, International Journal of Environmental Health Research, vol 15, issue 6, Taylor & Francis Ltd, UK, pp. 437-448.

Shenstone, L.L., Hyndman, R.J., 2005, Stochastic models underlying Croston's method for intermittent demand forecasting, Journal of Forecasting, vol 24, issue 6, John Wiley & Sons Ltd, UK, pp. 389-402.

Snyder, R.D., Koehler, A.B., Hyndman, R.J., Ord, J.K., 2004, Exponential smoothing models: means and variances for lead-time demand, European Journal of Operational Research, vol 158, issue 2, Elsevier BV, The Netherlands, pp. 444-455.

Hall, P., Hyndman, R.J., Fan, Y., 2004, Nonparametric confidence intervals for receiver operating characteristic curves, Biometrika, vol 91, issue 3, Oxford University Press, UK, pp. 743-750.

Smith, L., Hyndman, R.J., Wood, S.N., 2004, Spline interpolation for demographic variables: the monotonicity problem, Journal of Population Research, vol 21, issue 1, Australian Population Association, Australia, pp. 95-98.

Hyndman, R.J., 2004, The interaction between trend and seasonality, International Journal of Forecasting, vol 20, issue 4, Elsevier BV, The Netherlands, pp. 561-563.

Hall, P.G., Hyndman, R.J., 2003, Improved methods for bandwidth selection when estimating ROC curves, Statistics & Probability Letters, vol 64, issue 2, Elsevier BV, The Netherlands, pp. 181-189.

Rateau, F., Laumonier, B., Hyndman, R.J., 2003, Normative data for the Rosner Test of Visual Analysis Skills on an Australian population, Optometry and Vision Science, vol 80, issue 6, Lippincott Williams & Wilkins, USA, pp. 431-436.

Hyndman, R.J., Billah, M., 2003, Unmasking the Theta method, International Journal of Forecasting, vol 19, issue 2, Elsevier BV, The Netherlands, pp. 287-290.

Hyndman, R.J., Koehler, A.B., Snyder, R.D., Grose, S.D., 2002, A state space framework for automatic forecasting using exponential smoothing methods, International Journal of Forcasting, vol 18, issue 3, Elsevier Science, Netherland, pp. 439-454.

Cai, T., Hyndman, R.J., Wand, M., 2002, Mixed model-based hazard estimation, Journal of Computational and Graphical Statistics, vol 11, issue 4, American Statistical Association, USA, pp. 784-798.

Hyndman, R.J., Yao, Q., 2002, Nonparametric estimation and symmetry tests for conditional density functions, Journal of Nonparametric Studies, vol 14, issue 3, Taylor and Francis, UK, pp. 259-278.

Racine, J., Hyndman, R.J., 2002, Using R to teach econometrics, Journal of Applied Econometrics, vol 17, issue 2, John Wiley & Sons Ltd, UK, pp. 175-190.

Bashtannyk, D.M., Hyndman, R., 2001, Bandwidth selection for kernel conditional density estimation, Computational Statistics and Data Analysis, vol 36, Elsevier, Holland, pp. 279-298.

Predavec, M., Krebs, C.J., Danell, K., Hyndman, R., 2001, Cycles and synchrony in the collared lemming in Arctic North America, Oecologia, vol 126, Springer-Verlag, Germany, pp. 216-224.

Erbas, B., Hyndman, R.J., 2001, Data visualisation for time series in environmental epidemiology, Journal of Epidemiology and Biostatistics, vol 6, issue 6, Taylor & Francis, London UK, pp. 433-443.

Hyndman, R., 2001, It's time to move from 'what' to 'why', International Journal of Forecasting, vol 17, Elsevier, Holland, pp. 567-570.

Hyndman, R.J., Grunwald, G.K., 2000, Generalized additive modelling of mixed distribution Markov models with application to Melbourne's rainfall, Australian and New Zealand Journal of Statistics, vol 42 issue 2, Blackwell, Oxford UK, pp. 145-158.

Grunwald, G.K., Hyndman, R.J., Tedesco, L., Tweedie, R.L., 2000, Non-Gaussian conditional linear AR(1) models, Australian and New Zealand Journal of Statistics, vol 42 issue 4, Blackwell, Oxford UK, pp. 479-495.

Fraccaro, R., Hyndman, R.J., Veevers, A., 2000, Residual diagnostic plots for model mis-specification in time series regression, Australian and New Zealand Journal of Statistics, vol 42 issue 4, Blackwell, Oxford UK, pp. 463-477.

Hyndman, R.J., 1999, Review of book two books: A primer of mathematical writing; Handbook of writing for the mathematical sciences, Australian & New Zealand Journal of Statistics, vol 41, 2, Blackwell, Oxford, pp. 252-253.

Hyndman, R.J., 1999, Review of book: Chance encounters: A first course in data analysis and inference, Australian and New Zealand Journal of Statistics, vol 41, 4, Blackwell, Oxford UK, pp. 493-495.

Hyndman, R.J., 1999, Review of book: Statistically speaking: A dictionary of quotations, Australian and New Zealand Journal of Statistics, vol 41, 3, Blackwell, Oxford UK, pp. 380-382.

Hyndman, R.J., 1998, Review of "Leading Personalities in Statistical Science", Australian and New Zealand Journal of Statistics, vol 40, 3, Blackwell, Oxford, pp. 382-383.

Hyndman, R.J., 1998, Review of "Smoothing Methods in Statistics", Australian and New Zealand Journal of Statistics, vol 40, 2, Blackwell, Oxford, pp. 251-252.

Grunwald, G.K., Hyndman, R.J., 1998, Smoothing non-Gaussian time series with autoregressive structure, Computational Statistics and Data Analysis, vol 28, Elsevier, Amsterdam Netherlands, pp. 171-191.

Hyndman, R.J., Wand, M., 1997, Nonparametric Autocovariance Function Estimation, The Australian Journal of Statistics, vol 39, Australian Statistical Publishing Association Inc, Canberra ACT Australia, pp. 313-324.

Grunwald, G.K., Hamza, K., Hyndman, R.J., 1997, Some Properties and Generalizations of Non-negative Bayesian Time Series Models, Journal of the Royal Statististical Society Series B, vol 59, Royal Statistical Society, London UK, pp. 615-626.

Lajbcygier, P.R., Flitman, A., Swan, A., Hyndman, R.J., 1997, The Pricing and Trading of Options using a Hybrid Neural Network Model with Historical Volatility, Neurovest Journal, vol 5, Finance & Technology Publishing, Haymarket USA, pp. 27-41.

Lajbcygier, P.R., Flitman, A.M., Swan, A., Hyndman, R.J., 1997, The Pricing and Trading of Options using a Hybrid Neural Network with Historical Volatility, Journal of Computational Intelligence in Finance, vol 5, Finance & Technology, Haymarket VA USA, pp. 27-40.

Conference Proceedings

Villanova, L., Falcaro, P., Carta, D., Poli, I., Hyndman, R., Smith-Miles, K., 2010, Functionalization of microarray devices: process optimization using a multiobjective PSO and multiresponse MARS modeling, Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC), 18 July 2010 to 23 July 2010, IEEE-Institute of Electrical Electronic Engineers Inc, Atlanta USA, pp. 1-8.

Ye, A., Hyndman, R.J., Li, Z., 2006, Local linear multiple regression with variable bandwith in the presence of heteroskedasticity, Far Eastern Meeting of the Econometric Society (FEMES), 9 July 2006 to 12 July 2006, Far Eastern Meeting of the Econometric Society (FEMES), Beijing China, pp. 1-25.

Wang, X.C., Smith, K.A., Hyndman, R.J., 2005, Characteristic-based Forecasting for Time Series Data, 25th International Symposium on Forecasting, 12/06/2005 to 15/06/2005, The International Institute of Forecasters, San Antonia TX USA, p. 57.

Pitrun, I., King, M.L., Hyndman, R.J., 1999, A smoothing spline based test for non-linearity in a regression model, Proceedings: Queensland Finance Conference 1999, 30/9 - 1/10/99, Queensland University of Technology, Brisbane Qld Australia, pp. 1-18.

Hyndman, R.J., 1999, Nonparametric additive regression models for binary time series, Proceedings: ESAM99 (Econometric Society Australasian Meeting), Sydney, 7-9 July 1999, University of Technology, Sydney, Sydney NSW Australia, pp. 1-17.

Other

Hyndman, R.J., Gordon-Brown, L.N., Akram, M., Brown, P.G., 2002, Review of current arrangements for producing PBS forward estimates, Monash University Business & Economic Forecasting Unit, Clayton Vic Australia, pp. 1-280.

Hyndman, R.J., 1997, The Australian Journal of Statistics, Book Review Editor, Australian Statistical Publishing Association Inc., Australia.

Postgraduate Research Supervisions

Current Supervision

Program of Study:
(DOCTORATE BY RESEARCH).
Thesis Title:
Computation of Prediction Intervals for Optimal Combination Forecasts.
Supervisors:
Athanasopoulos, G (Joint), Hyndman, R (Joint-co).
Program of Study:
(MASTER'S BY RESEARCH).
Thesis Title:
Density forecasting using a functional data approach.
Supervisors:
Hyndman, R (Main), Poskitt, D (Associate).
Program of Study:
(DOCTORATE BY RESEARCH).
Thesis Title:
Forecasting for count time series.
Supervisors:
Hyndman, R (Main), Athanasopoulos, G (Associate).
Program of Study:
(DOCTORATE BY RESEARCH).
Thesis Title:
Forecasting of life tables and life expectancy: a functional data approach.
Supervisors:
Hyndman, R (Main), Poskitt, D (Associate).
Program of Study:
(DOCTORATE BY RESEARCH).
Thesis Title:
Singular spectrum analysis for times series forecasting.
Supervisors:
Hyndman, R (Joint), Poskitt, D (Joint-co).

Completed Supervision

Student:
Ahmed, R.
Program of Study:
Forecasting hierarchical time series. (PHD) 2008.
Supervisors:
Hyndman, R (Main), Athanasopoulos, G (Associate).
Student:
Akram, M.
Program of Study:
STABILITY PROPERTIES OF STATE SPACE MODELS FOR EXPONENTIAL SMOOTHING. (PHD) 2005.
Supervisors:
Hyndman, R (Main), King, M (Associate).
Student:
Arivalzahan, S.
Program of Study:
Discrimination and classification in functional data analysis. (PHD) 2007.
Supervisors:
Hyndman, R (Joint), Poskitt, D (Joint-Co).
Student:
Bashtannyk, D.
Program of Study:
Kernel conditional density estimation. (PHD) 2000.
Supervisors:
Hyndman, R (Main).
Student:
De Livera, A.
Program of Study:
Modeling time series with complex seasonal patterns using exponential smoothing. (PHD) 2010.
Supervisors:
Hyndman, R (Main), Snyder, R (Associate).
Student:
De Silva, A.
Program of Study:
The vector innovations structural time series framework. (PHD) 2007.
Supervisors:
Hyndman, R (Main), Snyder, R (Associate).
Student:
Hayat Muhammad, A.
Program of Study:
Identifying GDP volatility and modeling changing seasonality. (PHD) 2007.
Supervisors:
King, M (Main), Hyndman, R (Associate).
Student:
Khandakar, Y.
Program of Study:
Automatic ARIMA forecasting. (PHD) 2009.
Supervisors:
Hyndman, R (Main), Poskitt, D (Associate).
Student:
O'Reilly, H.
Program of Study:
A COMPARISON OF TRADING STRATEGIES FOR SHARE PRICE INDEX FUTURES. (Masters) 2003.
Supervisors:
Hyndman, R (Main).
Student:
Osman, A.
Program of Study:
A new approach to forecasting based on exponential smoothing with independent regressors. (PHD) 2012.
Supervisors:
Hyndman, R (Joint), King, M (Joint-Co).
Student:
Shang, H.
Program of Study:
Visualizing and forecasting functional time series. (PHD) 2010.
Supervisors:
Hyndman, R (Main), Poskitt, D (Associate).
Student:
Ullah, M.
Program of Study:
Demographic forecasting using functional data analysis. (PHD) 2006.
Supervisors:
Hyndman, R (Main).
Student:
Yasmeen, F.
Program of Study:
Functional linear models for mortality forecasting. (PHD) 2010.
Supervisors:
Hyndman, R (Main), Poskitt, D (Associate).