Identification and estimation of discrete state-vector models with stochastic inputs

PW Otter*

*Corresponding author for this work

    Research output: Contribution to journalComment/Letter to the editorAcademicpeer-review

    2 Citations (Scopus)

    Abstract

    The study deals with the identification and estimation of the unknown parameters of an ‘extended’ state-vector model, in which stochastic input variables are treated as ‘state’-variables and the observed input-values as ‘output’-values of the model.

    A parameter identifiability criterion, based on Fisher's information matrix, is applied to the model and a general ML-estimation procedure is given. If a certain restriction on the covariance-matrix of the state-vector is placed, the ML-procedure simplifies and coincides with an operational method, called the Lisrel procedure. This procedure provides also a test for parameter identifiability.
    Original languageEnglish
    Pages (from-to)389-391
    Number of pages3
    JournalAutomatica
    Volume17
    Issue number2
    DOIs
    Publication statusPublished - 1981

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