JOINT ASSESSMENT OF CHARACTERISTICS OF OBJECT PARAMETERS AND STATISTICAL CHARACTERISTICS OF DISTURBING INFLUENCES

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JOINT ASSESSMENT OF CHARACTERISTICS OF OBJECT PARAMETERS AND STATISTICAL CHARACTERISTICS OF DISTURBING INFLUENCES

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The paper considers the problem of joint estimation of object parameters and statistical characteristics of random disturbances based on data from independent experiments. It is indicated that the use of the method of moments for the problem under consideration gives estimates that are not effective in the Rao-Kramer sense and the most common asymptotically effective estimation method, in this sense, is the maximum likelihood method(ML). However, in the case of objects with several disturbances that have distribution densities of a general form, the implementation of the ML method is difficult, since to find the values of the distribution density it is necessary to calculate (q 1) -dimensional integrals. The presented minimum distance (MD) method can be applied to find joint estimates of the object parameters and the parameters of random disturbances. MD estimates with weight matrices independent of the parameters can be taken as consistent parameter estimates. It is noted that, in contrast to the method of moments, the MD method allows solving the identification problem in the case of disturbances with unlimited dispersions.

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# generalized method of moments# joint estimation# maximum likelihood method# minimum distance method

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https://eroi.uz/11.0008/A0225-0011

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