MULTIPLE EQUATION SYSTEMS WITH STATIONARY ERRORS.
The article reports on the development of an efficient estimation method when there is no set of independent random vectors and to prove some asymptotic theorems concerning the results. When a variable is assumed to be Gaussian, the likelihood function is established and maximized. The asymptotic di...
| Publicado en: | Econometrica Vol. 41; no. 2; pp. 299 - 321 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Mar1973
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=6857579&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 6857579 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00129682 ECN jtl: Econometrica issn: 00129682 maglogo: Y pubinfo: dt: Mar1973 vid: 41 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 6857579 10.2307/1913491 ppf: 299 ppct: 22 formats: tig: atl: MULTIPLE EQUATION SYSTEMS WITH STATIONARY ERRORS. aug: au: Hannan, E. J. Terrell, R. D. affil: The Australian National University su: Asymptotic expansions Difference equations Stochastic convergence Estimation theory Distribution (Probability theory) Central limit theorem Numerical analysis Mathematical functions Probability theory sug: subj: Asymptotic expansions Difference equations Stochastic convergence Estimation theory Distribution (Probability theory) Central limit theorem Numerical analysis Mathematical functions Probability theory ab: The article reports on the development of an efficient estimation method when there is no set of independent random vectors and to prove some asymptotic theorems concerning the results. When a variable is assumed to be Gaussian, the likelihood function is established and maximized. The asymptotic distribution for the maximum likelihood estimates can be found by removing the Gaussian assumption. The estimates are regarded as efficient if they had the same asymptotic distribution as the maximum likelihood estimates. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 1973 holdings: @attributes: islocal: N |
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