Geodesic
Parametric and nonparametric estimation for characteristics of randomized models under limited data (entropy approach)
Matematičeskoe modelirovanie, Tome 27 (2015) no. 3, pp. 63-85

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The paper presents a new approach to determination of dependencies between limited input and output data. It is based on randomized static and dynamic models and on estimation of the probabilistic characteristics of their parameters. The static and dynamic models are described by the functional polynomials. Entropy approach is developed for parametric and nonparametric estimation, for which generalized informational Boltzmann's and Fermi's entropies are used.
Keywords: randomized model, robustness, entropy functional, entropy function, variation of entropy functional, likelihood function, likelihood functional
Mots-clés : Volterra polinomials, multiplicative algorithms. 
@article{MM_2015_27_3_a4,
     author = {A. Yu. Popkov and Yu. S. Popkov},
     title = {Parametric and nonparametric estimation for characteristics of randomized models under limited data (entropy approach)},
     journal = {Matemati\v{c}eskoe modelirovanie},
     pages = {63--85},
     publisher = {mathdoc},
     volume = {27},
     number = {3},
     year = {2015},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MM_2015_27_3_a4/}
}
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A. Yu. Popkov; Yu. S. Popkov. Parametric and nonparametric estimation for characteristics of randomized models under limited data (entropy approach). Matematičeskoe modelirovanie, Tome 27 (2015) no. 3, pp. 63-85. http://geodesic.mathdoc.fr/item/MM_2015_27_3_a4/