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Maximum likelihood method in parametric approximation of density function by direct observations of its logarithm

DOI 10.18127/j19997493-201803-02

Keywords:

I.R. Dubov – Dr.Sc.(Eng.), Professor, Department of Computer Engineering and Control Systems, Vladimir State University named after A.&N. Stoletovs
E-mail: Ilya.r.dubov@gmail.com


An approach to the parametric approximation of univariate density function from direct observations of the logarithm of this function is considered. It is assumed that the function is an exponent of the polynomial. It is proposed within this approach to replace the general least-squares method by the maximum likelihood method in order to take into account asymmetrical form of the density of the direct observations errors. Numerical experiment is performed and a significant increase in the accuracy of the parameter estimation is demonstrated.

References:
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