Narrow search
Showing 1 - 10 of 23
Cover Image
Convergence and Persistence of Left-Right Political Orientations in The Netherlands 1978-1995
Franses, Philip Hans; Ooms, Marius; Eisinga, Eisinga, R. - Faculteit der Economische Wetenschappen, Erasmus … - 1997
also reveal a move to the common mid-point. Fractionally integrated time series models support the convergence thesis with … right-most and left-most party affiliates converging most rapidly. However, the convergence we find may be part of a … nonperiodic wave-like pattern were periods of convergence are alternated by periods of divergence. Future political conflicts may …
Persistent link: https://www.econbiz.de/10010731848
Cover Image
Modeling Trigonometric Seasonal Components for Monthly Economic Time Series
Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - Tinbergen Instituut - 2010
This discussion paper led to an article in <I>Applied Economics</I> (2013). Vol. 45, pages 3024-3034.<P> The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time...</p></i>
Persistent link: https://www.econbiz.de/10011255517
Cover Image
Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - Tinbergen Instituut - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log-density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian...
Persistent link: https://www.econbiz.de/10011261933
Cover Image
Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - Tinbergen Institute - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log-density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian...
Persistent link: https://www.econbiz.de/10009144743
Cover Image
Dynamic factors in periodic time-varying regressions with an application to hourly electricity load modelling
Dordonnat, Virginie; Koopman, Siem Jan; Ooms, Marius - In: Computational Statistics & Data Analysis 56 (2012) 11, pp. 3134-3152
A dynamic multivariate periodic regression model for hourly data is considered. The dependent hourly univariate time series is represented as a daily multivariate time series model with 24 regression equations. The regression coefficients differ across equations (or hours) and vary...
Persistent link: https://www.econbiz.de/10010617652
Cover Image
Modeling Trigonometric Seasonal Components for Monthly Economic Time Series
Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - Tinbergen Institute - 2010
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...
Persistent link: https://www.econbiz.de/10008838551
Cover Image
Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, Geert; Koopman, Siem Jan; Ooms, Marius - 2011
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear log-density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian...
Persistent link: https://www.econbiz.de/10010326501
Cover Image
Modeling Trigonometric Seasonal Components for Monthly Economic Time Series
Hindrayanto, Irma; Aston, John A.D.; Koopman, Siem Jan; … - 2010
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...
Persistent link: https://www.econbiz.de/10010325881
Cover Image
Periodic unobserved cycles in seasonal time series with an application to US unemployment
Koopman, Siem Jan; Ooms, Marius; Hindrayanto, Irma - 2006
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 introduced for exact maximum likelihood...
Persistent link: https://www.econbiz.de/10011350384
Cover Image
Estimating systematic continuous-time trends in recidivism using a non-Gaussian panel data model
Koopman, Siem Jan; Lucas, André; Ooms, Marius; … - 2007
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 conditions including the criminological climate....
Persistent link: https://www.econbiz.de/10011372520