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~person:"Scharth, Marcel"
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State space models
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importance sampling
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simulated maximum likelihood
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stochastic conditional duration
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Scharth, Marcel
Proietti, Tommaso
22
Koopman, Siem Jan
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Mazzi, Gian Luigi
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Koop, Gary
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Dijk, Herman K. van
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Frale, Cecilia
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Björk, Tomas
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Gupta, Rangan
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Lee, Kai Ming
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Marczak, Martyna
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Hammoudeh, Shawkat
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Kapetanios, George
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Kim, Won Joong
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Ord, J. Keith
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Petrella, Ivan
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Akram, Muhammad
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Beaumont, Adrian
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Giannone, Domenico
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Hyndman, Rob J.
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Schlicht, Ekkehart
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Athanasopoulos, George
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Cavicchioli, Maddalena
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Cross, Jamie
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Daniels, Robert
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1
Numerically accelerated importance sampling for nonlinear non-Gaussian
state
space
models
Koopman, Siem Jan
;
Lucas, André
;
Scharth, Marcel
-
2012
We introduce a new efficient importance sampler for nonlinear non-Gaussian
state
space
models
. We propose a general and …
Persistent link: https://www.econbiz.de/10011386179
Saved in:
2
Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian
State
Space
Models
Koopman, Siem Jan
;
Lucas, Andre
;
Scharth, Marcel
-
Tinbergen Instituut
-
2011
sampler for nonlinear non-Gaussian
state
space
models
. We propose a general and efficient likelihood evaluation method for …
Persistent link: https://www.econbiz.de/10011255569
Saved in:
3
Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian
State
Space
Models
Koopman, Siem Jan
;
Lucas, Andre
;
Scharth, Marcel
-
Tinbergen Institute
-
2011
We introduce a new efficient importance sampler for nonlinear non-Gaussian
state
space
models
. By combining existing …
Persistent link: https://www.econbiz.de/10008873337
Saved in:
4
Numerically Accelerated Importance Sampling for Nonlinear Non-Gaussian
State
Space
Models
Koopman, Siem Jan
;
Lucas, Andre
;
Scharth, Marcel
-
2011
We introduce a new efficient importance sampler for nonlinear non-Gaussian
state
space
models
. We propose a general and …
Persistent link: https://www.econbiz.de/10010325813
Saved in:
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