Can I read Estimation of unknown parameters in nonlinear and non-Gaussian state-space models on EtoBox?

Estimation of unknown parameters in nonlinear and non-Gaussian state-space models by Tanizaki H. is a nonfiction available to read on EtoBox.

What is Estimation of unknown parameters in nonlinear and non-Gaussian state-space models about?

For the last decade, various simulation-based nonlinear and non-Gaussian filters and smoothers have been proposed. In the case where the unknown parameters are included in the nonlinear and non-Gaussian system, however, it is very difficult to estimate the parameters together with the state variables, because the state-space model includes a lot of parameters in general and the simulation-based procedures are subject to the simulation errors or the sampling errors. Therefore, clearly, precise estimates of the parameters cannot be obtained (i.e., the obtained estimates may not be the global optima). In this paper, an attempt is made to estimate the state variables and the unknown parameters simultaneously, where the Monte Carlo optimization procedure is adopted for maximization of the likelihood function.

Who reads Estimation of unknown parameters in nonlinear and non-Gaussian state-space models?

Author

Tanizaki H.

Published

2000

Language

EN

Category

nonfiction

Subjects

Mathematics, Probability, Stem