Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Siem Jan Koopman"'
Publikováno v:
Journal of Applied Econometrics. 32:1003-1026
Summary We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear, non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when th
Publikováno v:
Journal of Applied Econometrics. 29:65-90
SUMMARY We consider the dynamic factor model and show how smoothness restrictions can be imposed on factor loadings by using cubic spline functions. We develop statistical procedures based on Wald, Lagrange multiplier and likelihood ratio tests for t
Autor:
Rutger Lit, Siem Jan Koopman
Publikováno v:
Journal of the Royal Statistical Society. Series A. Statistics in Society, 178(1), 167-186. Wiley-Blackwell
Koopman, S J M & Lit, R 2015, ' A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League ', Journal of the Royal Statistical Society, Series A (Statistics in Society), vol. 178, no. 1, pp. 167–186 . https://doi.org/10.1111/rssa.12042
Koopman, S J & Lit, R 2015, ' A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League ', Journal of the Royal Statistical Society. Series A. Statistics in Society, vol. 178, no. 1, pp. 167-186 . https://doi.org/10.1111/rssa.12042
Koopman, S J M & Lit, R 2015, ' A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League ', Journal of the Royal Statistical Society, Series A (Statistics in Society), vol. 178, no. 1, pp. 167–186 . https://doi.org/10.1111/rssa.12042
Koopman, S J & Lit, R 2015, ' A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League ', Journal of the Royal Statistical Society. Series A. Statistics in Society, vol. 178, no. 1, pp. 167-186 . https://doi.org/10.1111/rssa.12042
This discussion paper led to a publication in Journal of the Royal Statistical Society Series A , 2015, 178(1), 167-186. Attack and defense strengths of football teams vary over time due to changes in the teams of players or their managers. We develo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56d444ad9224154dce29ad05479254a0
https://research.vu.nl/en/publications/69189bae-f302-4355-8110-5ed6c3c98c70
https://research.vu.nl/en/publications/69189bae-f302-4355-8110-5ed6c3c98c70
Publikováno v:
Koopman, S J, Lucas, A & Scharth, M 2015, ' Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State Space Models ', Journal of Business and Economic Statistics, vol. 33, no. 1, pp. 114-127 . https://doi.org/10.1080/07350015.2014.925807
Koopman, S J, Lucas, A & Scharth, M 2015, ' Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models ', Journal of Business and Economic Statistics, vol. 33, no. 1, pp. 114-127 . https://doi.org/10.1080/07350015.2014.925807
Journal of Business and Economic Statistics, 33(1), 114-127. American Statistical Association
Koopman, S J, Lucas, A & Scharth, M 2015, ' Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian State-Space Models ', Journal of Business and Economic Statistics, vol. 33, no. 1, pp. 114-127 . https://doi.org/10.1080/07350015.2014.925807
Journal of Business and Economic Statistics, 33(1), 114-127. American Statistical Association
This paper led to a publication in the 'Journal of Business & Economic Statistics' , 2015, 33 (1), 114-127. We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c4d93d29e5ecbd51b419e3394c6d6989
https://research.vu.nl/en/publications/6dc57a01-37fe-4960-a0ab-7ad20f3eae7e
https://research.vu.nl/en/publications/6dc57a01-37fe-4960-a0ab-7ad20f3eae7e
Autor:
Andre Lucas, Siem Jan Koopman
Publikováno v:
Koopman, S J & Lucas, A 2008, ' A Non-Gaussian Panel Time series Model for Estimating and Decomposing Default Risk ', Journal of Business and Economic Statistics, vol. 26, no. 4, pp. 510-525 . https://doi.org/10.1198/073500108000000051
Journal of Business and Economic Statistics, 26(4), 510-525. American Statistical Association
Journal of Business and Economic Statistics, 26(4), 510-525. American Statistical Association
We model 1981-2005 quarterly default frequencies for a panel of U.S. firms in different rating and age classes from the Standard and Poor database. The data are decomposed into systematic and firm-specific risk components, where the systematic compon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2f45b9aabb1993288c78c640ce8f4b2
https://hdl.handle.net/1871.1/bd736495-4259-41bd-a424-0f2e2788ec96
https://hdl.handle.net/1871.1/bd736495-4259-41bd-a424-0f2e2788ec96
Autor:
Siem Jan Koopman, K.M. Lee
Publikováno v:
Studies in Nonlinear Dynamics and Econometrics, 8(2), 1-22. Berkeley Electronic Press
Koopman, S J & Lee, K M 2004, ' Estimating stochastic volatility models: a comparison of two importance samplers ', Studies in Nonlinear Dynamics and Econometrics, vol. 8, no. 2, pp. 1-22 . https://doi.org/10.2202/1558-3708.1210
Koopman, S J & Lee, K M 2004, ' Estimating stochastic volatility models: a comparison of two importance samplers ', Studies in Nonlinear Dynamics and Econometrics, vol. 8, no. 2, pp. 1-22 . https://doi.org/10.2202/1558-3708.1210
In this paper, we describe and compare two simulated Maximum Likelihood estimation methods for a basic stochastic volatility model. For both methods, the likelihood function is estimated using importance sampling techniques. Based on a Monte Carlo st