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Snyder, Ralph D. Ord, John Keith Hyndman, Rob J. Beaumont, Adrian King, Maxwell L. McLaren, Keith Robert Franses, Philip Hans Billah, Baki Petropoulos, Fotios Gardner, Everette S. Sermpinis, Georgios Thomakos, Dimitrios D. Tashman, Len Talagala, Thiyanga S. Talagala, Priyanga Dilini Syntetos, Aris A. Spiliotis, Evangelos Shang, Han Lin Rubaszek, Michał Todini, Ezio Rostami-Tabar, Bahman Reade, J. James Rapach, David E. Ramos, Patrícia Pinson, Pierre Pedregal, Diego J. Pedio, Manuela Pavia, José Manuel Thorarinsdottir, Thordis Trapero Arenas, Juan Ramón Billah, Md. Baki Fiorucci, Jose A. Vahid-Araghi, Farshid Gould, Phillip G. Leeds, Mark Willemain, Thomas R. Smart, Charles N. Schwarz, Henry F. Louzada, Francisco Pellegrini, Tiago R. Beaumont, Adrian N. Wang, Xiaoqian Miller, Don M. Williams, Dan Archibald, Blyth C. Grose, Simone D. Ziel, Florian Yusupova, Alisa Winkler, Robert L. Panapakidis, Ioannis Önkal, Dilek Cirillo, Pasquale Gönül, M. Sinan Gilliland, Michael Frazier, David T. Fiszeder, Piotr Ellison, Joanne Baets, Shari de Cordeiro, Clara Castle, Jennifer Grossi, Luigi Carnevale, Claudio Browell, Jethro Boylan, John E. Bijak, Jakub Bessa, Ricardo J. Ben Taieb, Souhaib Barrow, Devon K. All co-authors prognoseverfahren zeitreihenanalyse forecasting state space exponential smoothing zustandsraummodell time models series model selection intervals compositional approach method incorporating tracking signal variances seasonal damped monitoring processes changing look measures forecast accuracy comments using factors winters inventory control lead arima simple evaluation marktanteil messung measurement bewertung saisonkomponente wirtschaftsprognose practice optimising theta relationship methods view trend case single source error study outliers correlated seasonality empirical information criteria patented bootstrapping intermittent demand prediction new classes decisions potential users normalization framework automatic means multiplicative
Composed forecasting model time series analysis state space state space model model selection forecasting compositional compositional time space models incorporating tracking tracking signal signal state arma modell arma model series state space approach approach forecasting models forecasting smoothing methods space model model monitoring monitoring processes processes changing changing variances smoothing model selection forecasting forecasting time series forecasting look measures measures forecast forecast accuracy method forecasting demand prediction seasonal factors inventory control lead time time demand intervals arima arima models market shares market share seasonal component economic forecast forecasting practice practice forecasting time series approach models models optimising optimising theta theta method method relationship relationship state series exponential exponential smoothing methods view view damped damped trend trend incorporating variances incorporating models exponential smoothing exponential forecasting case case single single source source error error state space look accuracy study study outliers outliers exponential smoothing approach forecasting forecasting series correlated correlated seasonality seasonality empirical empirical information information criteria criteria time variances exponential accuracy comments using new
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Anne B. Koehler Alternative spellings: A. B. Koehler Anne Koehler Biblio: Tätig am Dep. of Decision Sciences, Miami Univ., Oxford, Ohio
Publishing years Series Working paper / Department of Econometrics and Business Statistics, Monash University (14) Report / Econometric Institute, Erasmus University Rotterdam (1) 
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