ON THE COMPUTATION OF FULL-INFORMATION MAXIMUM LIKELIHOOD ESTIMATES FOR NONLINEAR EQUATION SYSTEMS.

In this paper, the author generalizes the modified Newton method previously applied to the computation of full-information maximum likelihood estimates of parameters of a system of linear structural equations to the case of a system of nonlinear structural equations. The success of that method for l...

Descripción completa

Detalles Bibliográficos
Publicado en:Review of Economics & Statistics Vol. 55; no. 1; pp. 104 - 110
Autor principal: Chow, Gregory C.
Formato: Artículo
Publicado: MIT Press Feb73
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=4644980&site=ehost-live
header:
  @attributes:
    shortDbName: hlh
    uiTerm: 4644980
    longDbName: Humanities International Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        00346535
        RMS
      jtl: Review of Economics & Statistics
      issn: 00346535
      maglogo: N
    pubinfo:
      dt: Feb73
      vid: 55
      iid: 1
      pid: 776
      pub: MIT Press
    artinfo:
      ui:
        4644980
        10.2307/1928000
      ppf: 104
      ppct: 6
      formats:
      tig:
        atl: ON THE COMPUTATION OF FULL-INFORMATION MAXIMUM LIKELIHOOD ESTIMATES FOR NONLINEAR EQUATION SYSTEMS.
      aug:
        au: Chow, Gregory C.
      su:
        Linear systems
        Newton-Raphson method
        Equations
        Linear statistical models
        Estimation theory
        Autoregression (Statistics)
        Iterative methods (Mathematics)
        Stochastic processes
      sug:
        subj:
          Linear systems
          Newton-Raphson method
          Equations
          Linear statistical models
          Estimation theory
          Autoregression (Statistics)
          Iterative methods (Mathematics)
          Stochastic processes
      ab: In this paper, the author generalizes the modified Newton method previously applied to the computation of full-information maximum likelihood estimates of parameters of a system of linear structural equations to the case of a system of nonlinear structural equations. The success of that method for linear systems has stimulated author's present attempt to generalize it for nonlinear systems. The subject of maximum likelihood estimation of nonlinear simultaneous equation systems has been studied by authors. The estimation equations for nonlinear systems are derived, under the assumptions that each structural equation contains a distinct set of parameters, that the parameters are not subject to any linear restrictions, and that the (additive) residuals are serially uncorrelated. In order to appreciate the nature and the difficulty of estimating the parameters of non-linear equations, it is useful to present the estimating equations when any structural equation is linear. It is also of practical importance to do so, since linear structural equations are often encountered in practice, and one would wish to exploit the linearity to simplify computations.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: Y
      dt:
        @attributes:
          year: 1973
    holdings:
      @attributes:
        islocal: N