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ENVIRONMENTAL-ECONOMIC DIAGNOSTIC OF ENTERPRISES ON THE BASIS OF MULTIVARIATE STATISTICAL METHODS of multivariate statistical methods in the analysis and associated problems is discussed. On the example of oil

Multiple regression as a method of construction of isolines of animal response to a joint effect of two factors (using the vocal activity of the steppe marmot as an example).Multiple regression as a method of construction of isolines of animal response to a joint effect

Can invasive plant species "differentiate" colonized ecotopes?The article presents the analysis and results of the application of traditional research methods

Environmental-economic indicators of the sustainability of the enterprises of oil and gas complex of multivariate statistical methods realized the estimation of the informativity of different indicators

Parsimonious models of multivariate binary time series: statistical estimation and forecastingThis paper is devoted to parsimonious models of multivariate binary time series. Consistent

METHODS OF SEX ESTIMATION FROM THE CLAVICLES IN FORENSIC EXAMINATION OF BONE REMAINS was to develop new methods for sex determination from the clavicle of an adult person based on the mathematical

Analysis and assessment of heavy metal contamination in the vicinity of Lake Atamanskoe (Rostov region, Russia) using multivariate statistical methods chemistry. In this study, descriptive statistics and three methods of multivariate statistical analysis

Labor productivity as a factor for increasing public production efficiency for calculating the multivariate average value of production resources is used in order to identify the role

Application of cluster and discriminant analyses to diagnose lithological heterogeneity of the parent material according to its particle-size distribution to distinguish between alluvial and colluvial sediments have been calculated. Statistical assessment of particle

Oil and Gas Perspective Assessment and the Choice of the Exploration Program based on the Multivariate Geological Modeling to the predicted one. The method brings together advantages of multi-version geological modeling and statistical

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