Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation

Christoph Bergmeir1, Rob J Hyndman2, José M Benítez1 Department of Computer Science and Artificial Intelligence, University of Granada, Spain. Department of Econometrics and Business Statistics, Monash University, Australia. Abstract: Exponential smoothing is one of the most popular forecasting methods. We present a method for bootstrap aggregation (bagging) of exponential smoothing

Read More

Nonparametric and semiparametric response surface methodology: a review of designs, models and optimization techniques

Laura Villanova, Rob J Hyndman, Kate Smith-Miles, Irene Poli Abstract: Since the introduction of Response Surface Methodology in the 1950s, there have been many developments with the aim of expanding the range of applications of the methodology. Various new design, modeling and optimization techniques have been introduced for coping with unknown

Read More

A state space model for exponential smoothing with group seasonality

Pim Ouwehand1 , Rob J Hyndman2 , Ton G. de Kok1 and Karel H. van Donselaar1 Department of Technology Management, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven, The Netherlands. Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia. Abstract We present an approach to improve

Read More

Local linear multivariate regression with variable bandwidth in the presence of heteroscedasticity

Azhong Ye1 , Rob J Hyndman2 and Zinai Li3 College of Management, Fuzhou University, Fuzhou, 350002, China. Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia. School of Economics and Management, Tsinghua University, Beijing, 100084, China. Abstract We present a local linear estimator with variable bandwidth for multivariate

Read More

Time series forecasting: the case for the single source of error state space approach

J. Keith Ord1 , Ralph D. Snyder2 , Anne B. Koehler3 , Rob J. Hyndman2 and Mark Leeds4 320 Old North, Georgetown University, Washington, DC 20057, USA. Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia. Department of Decision Sciences and Management Information Systems, Miami University, Oxford, OH

Read More

Seasonal adjustment methods for the analysis of respiratory disease in environmental epidemiology

Bircan Erbas1 and Rob J Hyndman2 Department of General Practice & Public Health, The University of Melbourne, VIC 3010, Australia. Department of Econometrics and Business Statistics, Monash University, VIC 3800, Australia. Abstract We study the relationship between daily hospital admissions for respiratory disease and various pollutant and climatic variables, looking

Read More

A unified view of linear AR(1) models

Grunwald, G.K., Hyndman, R.J., and Tedesco, L. Abstract We review and synthesize the wide range of non-Gaussian first order linear autoregressive models that have appeared in the literature. Models are organized into broad classes to clarify similarities and differences and facilitate application in particular situations. General properties for process mean,

Read More