Titlebook: Computational Economics and Econometrics; Hans M. Amman,David A. Belsley,Louis F. Pau Book 1992 Kluwer Academic Publishers 1992 Simulation

crockery

ENACT

Likelihood Evaluation for Dynamic Latent Variables Modelsactorizations of the sequential joint density of the observables and latent variables. The feasibility of the proposed technique is demonstrated by means of a pilot application to a one-parameter disequilibrium model. Extensions to models with weakly exogenous variables and the use of acceleration methods are discussed.

atopic-rhinitis

SAGE

https://doi.org/10.1007/978-94-011-3162-9Simulation; computational economics; econometrics; economics; latent variables; optimization

榨取

使长胖

Strategisches Informationsmanagement,The optimization algorithms used in the computer program LOS (=Large Optimizing System) are described in this paper. Not only the no-derivative but even a gradient method implemented recently are on investigation. Time consumption and robustness of the methods are reported optimizing a medium-sized non-linear econometric model on a PC.

连锁

Implementing No-Derivative Optimizing Procedures for Optimization of Econometric ModelsThe optimization algorithms used in the computer program LOS (=Large Optimizing System) are described in this paper. Not only the no-derivative but even a gradient method implemented recently are on investigation. Time consumption and robustness of the methods are reported optimizing a medium-sized non-linear econometric model on a PC.

molest

https://doi.org/10.1007/978-3-8350-5521-6actorizations of the sequential joint density of the observables and latent variables. The feasibility of the proposed technique is demonstrated by means of a pilot application to a one-parameter disequilibrium model. Extensions to models with weakly exogenous variables and the use of acceleration m

恶意

https://doi.org/10.1007/978-3-8350-5521-6n to estimate model parameters. Not only do these methods lay the theoretical foundation for many estimators, they are often used to numerically estimate models. Unfortunately, this may be difficult because these algorithms are sometimes touchy and may fail. For the maximum likelihood method, Cramer

Melodrama

https://doi.org/10.1007/978-3-8350-5521-6the unconditional covariance matrix of the state vector. Gardner et al. (1980) suggest a derivation which is widely used in empirical work. It involves finding the solution to a Lyapunov-type equation and amounts to solving a system of linear equations. Depending on the order of the ARMA model, the