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On importance sampling for state space models

Jungbacker, Borus; Koopman, Siem Jan - 2005

Persistent link: https://www.econbiz.de/10003248123

Parameter driven multi-state duration models : simulated vs. approximate maximum likelihood estimation

Monteiro, André Antonio - 2008

Persistent link: https://www.econbiz.de/10003690030

Long memory modelling of inflation with stochastic variance and structural breaks

Bos, Charles S.; Koopman, Siem Jan; Ooms, Marius - 2007

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

Persistent link: https://www.econbiz.de/10011373822

Parameter driven multi-state duration models : simulated vs. approximate maximum likelihood estimation

Monteiro, André Antonio - 2008 - This version: February 15, 2008

evaluating the likelihood, two of the methods rely on Monte Carlo integration with importance sampling techniques. The third …

Persistent link: https://www.econbiz.de/10011374420

Model-based measurement of actual volatility in high-frequency data

Jungbacker, Borus; Koopman, Siem Jan - 2004

are based on importance sampling techniques. It is shown that such Monte Carlo techniques can be employed successfully for …

Persistent link: https://www.econbiz.de/10011342558

On Importance Sampling for State Space Models

Jungbacker, Borus; Koopman, Siem Jan - 2006

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … are presented that lead to a more effective implementation of importance sampling for state space models. An illustration …

Persistent link: https://www.econbiz.de/10014060268