Bayesian predictions of low count time series
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Bibliographic InfoArticle provided by Elsevier in its journal International Journal of Forecasting.
Volume (Year): 21 (2005)
Issue (Month): 2 ()
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- B.P.M. McCabe & G.M. Martin & R.K. Freeland, 2004.
"Testing for Dependence in Non-Gaussian Time Series Data,"
Monash Econometrics and Business Statistics Working Papers
13/04, Monash University, Department of Econometrics and Business Statistics.
- Keith Freeland & Brendan McCabe & Gael Martin, 2004. "Testing for Dependence in Non-Gaussian Time Series Data," Econometric Society 2004 Australasian Meetings 313, Econometric Society.
- Durbin, J. & Koopman, S.J.M., 1998.
"Time Series Analysis of Non-Gaussian Observations Based on State Space Models from Both Classical and Bayesian Perspectives,"
1998-142, Tilburg University, Center for Economic Research.
- J. Durbin & S. J. Koopman, 2000. "Time series analysis of non-Gaussian observations based on state space models from both classical and Bayesian perspectives," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 3-56.
- Robert C. Jung & A. R. Tremayne, 2003. "Testing for serial dependence in time series models of counts," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(1), pages 65-84, 01.
- Brännäs, Kurt & Hellström, Jörgen, 1999.
"Generalized Integer-Valued Autoregression,"
UmeÃ¥ Economic Studies
501, Umeå University, Department of Economics.
- R. K. Freeland & B. P. M. McCabe, 2004. "Analysis of low count time series data by poisson autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 701-722, 09.
- Chib, Siddhartha & Greenberg, Edward & Winkelmann, Rainer, 1998.
"Posterior simulation and Bayes factors in panel count data models,"
Journal of Econometrics,
Elsevier, vol. 86(1), pages 33-54, June.
- Siddhartha Chib & Edward Greenberg & Rainer Winkelmann, 1996. "Posterior Simulation and Bayes Factors in Panel Count Data Models," Econometrics 9608003, EconWPA, revised 25 Nov 1996.
- Chib, Siddhartha & Winkelmann, Rainer, 2001. "Markov Chain Monte Carlo Analysis of Correlated Count Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(4), pages 428-35, October.
- Freeland, R. K. & McCabe, B. P. M., 2004. "Forecasting discrete valued low count time series," International Journal of Forecasting, Elsevier, vol. 20(3), pages 427-434.
- Kleibergen, Frank, 2004. "Invariant Bayesian inference in regression models that is robust against the Jeffreys-Lindley's paradox," Journal of Econometrics, Elsevier, vol. 123(2), pages 227-258, December.
- Timothy Christensen & Stan Hurn & Kenneth Lindsay, 2009.
"It Never Rains but it Pours: Modeling the Persistence of Spikes in Electricity Prices,"
The Energy Journal,
International Association for Energy Economics, vol. 0(Number 1), pages 25-48.
- T M Christensen & A S Hurn & K A Lindsay, 2008. "It never rains but it pours: Modelling the persistence of spikes in electricity prices," NCER Working Paper Series 25, National Centre for Econometric Research.
- Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
- Yelland, Phillip M., 2010. "Bayesian forecasting of parts demand," International Journal of Forecasting, Elsevier, vol. 26(2), pages 374-396, April.
- De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
- Jung, Robert C. & Tremayne, A.R., 2006. "Coherent forecasting in integer time series models," International Journal of Forecasting, Elsevier, vol. 22(2), pages 223-238.
- T M Christensen & A. S. Hurn & K A Lindsay, 2008. "Discrete time-series models when counts are unobservable," NCER Working Paper Series 35, National Centre for Econometric Research.
- Drost, F.C. & Akker, R. van den & Werker, B.J.M., 2007. "Efficient Estimation of Autoregression Parameters and Innovation Distributions for Semiparametric Integer-Valued AR(p) Models (Subsequently replaced by DP 2008-53)," Discussion Paper 2007-23, Tilburg University, Center for Economic Research.
- Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
- Andersson, Jonas & Karlis, Dimitris, 2008. "Treating missing values in INAR(1) models," Discussion Papers 2008/14, Department of Business and Management Science, Norwegian School of Economics.
- Ng, Jason & Forbes, Catherine S. & Martin, Gael M. & McCabe, Brendan P.M., 2013.
"Non-parametric estimation of forecast distributions in non-Gaussian, non-linear state space models,"
International Journal of Forecasting,
Elsevier, vol. 29(3), pages 411-430.
- Jason Ng & Catherine S. Forbes & Gael M. Martin & Brendan P.M. McCabe, 2011. "Non-Parametric Estimation of Forecast Distributions in Non-Gaussian, Non-linear State Space Models," Monash Econometrics and Business Statistics Working Papers 11/11, Monash University, Department of Econometrics and Business Statistics.
- Francesco Bravo, 2011. "Comment on: Subsampling weakly dependent time series and application to extremes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer, vol. 20(3), pages 483-486, November.
- Yelland, Phillip M., 2009. "Bayesian forecasting for low-count time series using state-space models: An empirical evaluation for inventory management," International Journal of Production Economics, Elsevier, vol. 118(1), pages 95-103, March.
- Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
- Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
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