1994
DOI: 10.1515/rnam.1994.9.4.395
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On identifiability of mathematical models of evolutionary processes from data of discrete measurements of state vector

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Cited by 3 publications
(4 citation statements)
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“…The existence of a minimum value of the sum of squares of deviations Φ(α|£7) is intuitively understandable and theoretically justified [2,4,6,[9][10][11][12]. However, in any case the question arises of whether a point of minimum is unique for the considered functional Φ(α|ί/).…”
Section: G T [X(t) -X (T A)}mentioning
confidence: 99%
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“…The existence of a minimum value of the sum of squares of deviations Φ(α|£7) is intuitively understandable and theoretically justified [2,4,6,[9][10][11][12]. However, in any case the question arises of whether a point of minimum is unique for the considered functional Φ(α|ί/).…”
Section: G T [X(t) -X (T A)}mentioning
confidence: 99%
“…The generalization to the case of indirect measurements can be found in our previous publications [10,11]. Besides, it should be noted that in the subsequent discussion the observational data is interpreted as realisations of a random process for the reason that the data is measurement results [9,[10][11][12].…”
Section: G T [X(t) -X (T A)}mentioning
confidence: 99%
“…Unfortunately, the system of genetic ecological monitoring has not been developed in Russia [4]. Therefore it is necessary to schedule the measures intended for collecting and processing the experimental data in order for the conditions for the identifiability of the mathematical model used [14,15,17] to be satisfied.…”
Section: U(t) « Ui ^ Tto V(£) « VI £ Vqmentioning
confidence: 99%
“…Using different approaches to the solution of problems of the parametric identification of mathematical models of evolutionary processes with lumped parameters by the limited experimental data on the state vector [14,15,17], we can determine not only the estimate of the extended parameter vector α of the mathematical model (1.1) but also its a posteriori distribution law. Thus, having solved the parametric identification problem, the state vector of the population X(t,a,Xo) is a vector random process, and according to conventional terminology [11] we obtain a problem of taking dicisions under risk conditions.…”
Section: U(t) « Ui ^ Tto V(£) « VI £ Vqmentioning
confidence: 99%