Statistical Methods in Virtualization
https://doi.org/10.1134/S2304487X19060063
Abstract
Essential component of virtual tool is statistical one used for statistical models identification on qualification tests results, criteria models parameterization for forecasting at qualification tests, regression models synthesis, their optimization and adequateness analysis at factor planning. Regression model linearity allows controlling factors significance using standard statistical methods and performing model optimization using linear programming. At oils characteristics identification their non-normality was shown. To form rational processing algorithms some alternative approximations were formed. Bimodal density distribution was approximated with sum of different normal ones. One – modal distributions of other characteristics were approximated with Weibull distributions. Parameterization of these distributions was performed using moment’s method. For reproducibility estimation analytical Cochran distribution on the base of Fisher distribution and analytical Grabbs distribution on the base of Student distribution were developed. It was shown that preliminary normalization allows avoiding error decision about result reproducibility. Criteria model parameterization was proposed to perform on effect forecast at extremal conditions that allows to guaranty qualification normative. Preliminary choice of these conditions is realized by using step-by-step approach in the course of factor analysis. Developed method for similarity criteria synthesis is based on criterion logarithm presentation as linear form of some similarity numbers interpreted as independent factors. Coefficients of this form were estimated using factor analysis. Also the intuitive method of factors ranking in linear form using saturated plans and least significant factors rejection was developed. Its base advantage is fictive factors exclusion and base disadvantage – regular method absence for significance thresholds set.
Keywords
tool,
identification,
parameterization,
criteria model,
forecasting,
regression model,
factor planning,
linear programming,
bimodal distribution,
approximation,
Cochran statistics,
Grabbs statistics,
qualification normative,
similarity criterion,
similarity number,
fictive factor,
significance,
ranking
About the Author
A. А. Moiseev
NPP Technos-RM (Technos-RM Research and Production Enterprise)
Russian Federation
Russian Federation
141002
Mytischi
References
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Review
For citations:
Moiseev A.А. Statistical Methods in Virtualization. Vestnik natsional'nogo issledovatel'skogo yadernogo universiteta "MIFI". 2020;9(1):66-81. (In Russ.) https://doi.org/10.1134/S2304487X19060063
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