Zobrazeno 1 - 10
of 66
pro vyhledávání: '"Marius Ooms"'
Publikováno v:
Journal of Statistical Software, Vol 41, Iss 01 (2011)
In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods
Externí odkaz:
https://doaj.org/article/4e363cdad8714058a0ee8ffde5571cd1
Publikováno v:
Hindrayanto, A I W, Aston, J A D, Koopman, S J & Ooms, M 2013, ' Modeling trigonometric seasonal components for monthly economic time series ', Applied Economics, vol. 45, no. 21, pp. 3024-3034 . https://doi.org/10.1080/00036846.2012.690937
Applied Economics, 45(21), 3024-3034. Routledge
Hindrayanto, I, Aston, J A D, Koopman, S J & Ooms, M 2013, ' Modelling trigonometric seasonal components for monthly economic time series ', Applied Economics, vol. 45, no. 21, pp. 3024-3034 . https://doi.org/10.1080/00036846.2012.690937
Applied Economics, 45(21), 3024-3034. Routledge
Hindrayanto, I, Aston, J A D, Koopman, S J & Ooms, M 2013, ' Modelling trigonometric seasonal components for monthly economic time series ', Applied Economics, vol. 45, no. 21, pp. 3024-3034 . https://doi.org/10.1080/00036846.2012.690937
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this article, we explore a generalization of the basic structural time series model in which the time-varying trigonometri
Publikováno v:
Econometric Reviews, 35(4), 659-687. Taylor and Francis Ltd.
Mesters, G, Koopman, S J & Ooms, M 2016, ' Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models ', Econometric Reviews, vol. 35, no. 4, pp. 659-687 . https://doi.org/10.1080/07474938.2015.1031014
Mesters, G, Koopman, S J & Ooms, M 2016, ' Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models ', Econometric Reviews, vol. 35, no. 4, pp. 659-687 . https://doi.org/10.1080/07474938.2015.1031014
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f55f252142c81ad70250e65b139d8566
https://research.vu.nl/en/publications/cd05c4b6-08bb-477b-95b8-2137d816a135
https://research.vu.nl/en/publications/cd05c4b6-08bb-477b-95b8-2137d816a135
Publikováno v:
Age and Ageing, 40(2), 211-214
Age and Ageing, 40(2), 211-214. Oxford University Press
Chel, V G M, Ooms, M E, Pavel, S, de Gruijl, F, Brand, A & Lips, P T A M 2011, ' Prevention and treatment of vitamin D deficiency in Dutch psychogeriatric nursing home residents by weekly half-body UVB exposure after showering: a pilot study ', Age and Ageing, vol. 40, no. 2, pp. 211-214 . https://doi.org/10.1093/ageing/afq159
Age and Ageing, 40(2), 211-214. Oxford University Press
Chel, V G M, Ooms, M E, Pavel, S, de Gruijl, F, Brand, A & Lips, P T A M 2011, ' Prevention and treatment of vitamin D deficiency in Dutch psychogeriatric nursing home residents by weekly half-body UVB exposure after showering: a pilot study ', Age and Ageing, vol. 40, no. 2, pp. 211-214 . https://doi.org/10.1093/ageing/afq159
Background: in older people, induction of cutaneous vitamin D production by ultraviolet B (UVB) exposure may be preferable to oral supplementation: it cannot cause toxic levels, it helps to prevent polypharmacy and, moreover, there are indications th
Autor:
Marius Ooms, Siem Jan Koopman
Publikováno v:
International Journal of Forecasting. 26:647-651
Publikováno v:
Koopman, S J, Hindrayanto, A I W & Ooms, M 2010, ' Exact maximum likelihood estimation for non-stationary periodic time series models ', Computational Statistics and Data Analysis, vol. 54, pp. 2641-2654 . https://doi.org/10.1016/j.csda.2010.04.010
Computational Statistics and Data Analysis, 54, 2641-2654. Elsevier
Computational Statistics and Data Analysis, 54, 2641-2654. Elsevier
Time series models with parameter values that depend on the seasonal index are commonly referred to as periodic models. Periodic formulations for two classes of time series models are considered: seasonal autoregressive integrated moving average and
Publikováno v:
Koopman, S J, Ooms, M & Hindrayanto, A I W 2009, ' Periodic unobserved cycles in seasonal time series with an application to U.S. unemployment ', Oxford Bulletin of Economics and Statistics, vol. 71, pp. 683-713 . https://doi.org/10.1111/j.1468-0084.2009.00557.x
Oxford Bulletin of Economics and Statistics, 71, 683-713. Wiley-Blackwell
Oxford Bulletin of Economics and Statistics, 71, 683-713. Wiley-Blackwell
This paper discusses identification, specification, estimation and forecasting for a general class of periodic unobserved components time series models with stochastic trend, seasonal and cycle components. Convenient state space formulations are intr
Autor:
Jurgen A. Doornik, Marius Ooms
Publikováno v:
Ooms, M & Doornik, J A 2008, ' Multimodality in GARCH regression models ', International Journal of Forecasting, vol. 24, no. 3, pp. 432-448 . https://doi.org/10.1016/j.ijforecast.2008.06.002
International Journal of Forecasting, 24(3), 432-448. Elsevier
International Journal of Forecasting, 24(3), 432-448. Elsevier
It is shown empirically that mixed autoregressive moving average regression models with generalized autoregressive conditional heteroskedasticity (Reg-ARMA-GARCH models) can have multimodality in the likelihood that is caused by a dummy variable in t
Publikováno v:
Statistica Neerlandica. 62:104-130
We model panel data of crime careers of juveniles from a Dutch Judicial Juvenile Institution. The data are decomposed into a systematic and an individual-specific component, of which the systematic component reflects the general time-varying conditio
Publikováno v:
Ooms, M, Koopman, S J & Carnero, A M 2007, ' Periodic Seasonal Reg-ARFIMA-GARCH Models for Daily Electricity Spot Prices ', Journal of the American Statistical Association, vol. 102, no. 477, pp. 16-27 . https://doi.org/10.1198/016214506000001022
Journal of the American Statistical Association, 102(477), 16-27. Taylor and Francis Ltd.
Journal of the American Statistical Association, 102(477), 16-27. Taylor and Francis Ltd.
Novel periodic extensions of dynamic long-memory regression models with autoregressive conditional heteroscedastic errors are considered for the analysis of daily electricity spot prices. The parameters of the model with mean and variance specificati