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- W2328562310 abstract "We consider a general non-linear multivariate time series model which can be parameterized by a finite and fixed number of parameters and which can be rewritten, if necessary, in a form such that the disturbances are stationary martingale differences. Given a series of discrete, equally spaced observations we prove the strong consistency and asymptotic normality of the Gaussian estimators of the parameters, the parameters possibly being subject to non-linear constraints. Because the normal equations are usually highly non-linear it may be difficult to obtain explicit expressions for the Gaussian estimates. To overcome this problem we use a Gauss–Newton type algorithm to obtain a sequence of iterates which converge to, and have the same asymptotic properties as, the Gaussian estimates." @default.
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- W2328562310 date "1978-06-01" @default.
- W2328562310 modified "2023-09-25" @default.
- W2328562310 title "Asymptotic properties of time domain gaussian estimators" @default.
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- W2328562310 doi "https://doi.org/10.2307/1426939" @default.
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