Un método de inicialización del filtrado para modelos en espacio de los estados con inputs estocásticos
dc.contributor.author | Casals Carro, José | |
dc.contributor.author | Sotoca López, Sonia | |
dc.date.accessioned | 2023-06-21T01:38:47Z | |
dc.date.available | 2023-06-21T01:38:47Z | |
dc.date.issued | 1996-09 | |
dc.description.abstract | En este trabajo se derivan las expresiones exactas de la media y varianza condicional del estado inicial de un modelo en espacio de los estados con inputs estocásticos, generalizando los resultados teóricos obtenidos por De Jong y Chu-Chun-Lin (1994). Se muestra que las condiciones iniciales exactas dependen del carácter estacionario o no estacionario del modelo y que las estimaciones finales de los parámetros son sensibles a la presencia de inputs estocásticos, siendo ésta una situación frecuente en Econometría. | |
dc.description.abstract | We derive exact expressions for the conditional mean and variance of the initial state of a state space system with stochastic inputs, under stationarity or nonstationarity. These results generalize those of De Jong and Chu-Chun-Lin (1994) and provide a useful initialization method to obtain maximum likelihood estimates of the model parameters. As final estimates are sensitive to initial conditions, the presence of stochastic inputs -a frequent situation ín Econometrics- should be considered when computing the mean and variance of the initial state. | |
dc.description.faculty | Fac. de Ciencias Económicas y Empresariales | |
dc.description.faculty | Instituto Complutense de Análisis Económico (ICAE) | |
dc.description.refereed | TRUE | |
dc.description.status | pub | |
dc.eprint.id | https://eprints.ucm.es/id/eprint/30533 | |
dc.identifier.relatedurl | http://www.ucm.es/icae | |
dc.identifier.uri | https://hdl.handle.net/20.500.14352/64242 | |
dc.issue.number | 10 | |
dc.language.iso | spa | |
dc.page.total | 22 | |
dc.publication.place | Madrid, España | |
dc.publisher | Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE) | |
dc.relation.ispartofseries | Documentos de Trabajo del Instituto Complutense de Análisis Económico | |
dc.rights | Atribución-NoComercial 3.0 España | |
dc.rights.accessRights | open access | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/3.0/es/ | |
dc.subject.jel | C32 | |
dc.subject.jel | C40 | |
dc.subject.keyword | Procesos estocásticos | |
dc.subject.keyword | Varianza condicional. | |
dc.subject.keyword | Initial conditions | |
dc.subject.keyword | Stationarity | |
dc.subject.keyword | Kalman filter | |
dc.subject.keyword | Exact maximum likelihood | |
dc.subject.keyword | State space models. | |
dc.subject.ucm | Econometría (Economía) | |
dc.subject.unesco | 5302 Econometría | |
dc.title | Un método de inicialización del filtrado para modelos en espacio de los estados con inputs estocásticos | |
dc.type | technical report | |
dc.volume.number | 1996 | |
dcterms.references | Anderson, B.D.O. yMoore, J.B. (1979). Optimal Filtering. Englewood Cliffs. NJ: Prentice Hall. Burridge, P. Y Wallis, K.F: (1985).Calculating the variance of seasonally adjusted series. Journal of the American Statistical Association, 80, 541-552. Danyang, L. y Xuanhuang, L. (1994). Optimal State Estimation without the Requirement of a Priori Statistics Information of the Initial state. IEEE Transactions on Automatic Control, 39, 10, 2087-2091. De Jong, P. (1988). The likelihood far a State Space Model. Biometrika 15, 1, 165-169. De Jong, P. Y Chu-Chun-Lin, S. (1994). Stationary and Non-Stationary State Space Models. Journal of Time Series Analysis, 15, 2, 151-166. García-Ferrer, A., del Hoyo, J., Novales, A. y Young, P.C. (1996). Recursive identification, estimation and forecasting of Nonstationary Economic Time Series with Applications to GNP International Data, en Bayesian Analysis in Statistics and Econometrics, Essays in Honor of Arnold Zellner , (eds., D.A. Berry, K.M. Chaloner and J.K. Geweke), John Wiley and Sons, Inc. Gardner, G., Harvey, A.C., y Phillips, G.D.A. (1980). Algorithm 154. An Algorithm for Exact Maximum-Likelihood Estimation of Autoregressive-Moving Average Models by Means of Kalman Filtering. Applied Statistics, 29, 311-317. Kitagawa, G. (1981). A Nonstationary Time Series Model and its Fitting by Recursive Filter. Journal of Time Series Analysis, 2, 103-116. Marshall, P. (1992). State Space Models with Diffuse Initial Conditions. Journal of Time Series Analysis, 13, 5, 411-414. Mauricio, J.A. (1995). Exact Maximum Likelihodd Estimation of Stationary Vector ARMA Models. Journal of the American Statistical Association, 90, 429, 282-291. Petkov, P.Hr., Christov, N.D. y Konstantinov, M.M. (1991). Computational Methods for Linear Control Systems. Prentice-Hall, Englewood Cliffs, N.J. Rosenberg, B. (1973). The Analysis of a Cross Section of Time Series by Stochastically Convergent Parameter Regression. Annals of Economic and Social Measurement, 2, 4, 399-428. Shea, B.L. (1987). Estimation of Multivariate Time Series. Journal of Time Series Analys1s, 8, 95-109. Sotoca, S. (1994). Aplicación del Filtro de Chandrasekhar a la Estimación por Máxima Verosimilitud Exacta de Modelos Dinámicos. Estadística Española, 36, 136, 259 285. Terceiro, J. (1990). Estimation of Dynamic Econometric Models with Errors in Variables. Springer-Verlag, Heidelberg. | |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 138478db-3f49-41e4-a76e-ff6d03e56bb8 | |
relation.isAuthorOfPublication.latestForDiscovery | 138478db-3f49-41e4-a76e-ff6d03e56bb8 |
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