scholarly journals ECONOMETRICAL MODELING OF THE STRUCTURE OF MULTIDIMENSIONAL STATISTICAL INTERRELATIONS

2019 ◽  
Vol 8 (6) ◽  
Author(s):  
Alexander K. Rozentsvaig ◽  
Aleksej G. Isavnin ◽  
Anton N. Karamyshev
Keyword(s):  
Statistical Analysis ◽  
Statistical Models ◽  
Information Technologies ◽  
Sampled Data ◽  
Distribution Law ◽  
Multivariate Statistical ◽  
Correlation Matrices ◽  
Multidimensional Distribution ◽  
Theoretical Concepts ◽  
Economic Phenomenon

In economics, the general theory is largely descriptive, and mathematical models are not only statistical but also partial. Therefore, an economic phenomenon usually requires using partial methods and getting only private solutions limited by particular conditions - the type of activity, its place and time of implementation. The real idea of the nature of the economic phenomenon that interests us is given only by statistical data. Correlation analysis is a time-consuming and completely non-formalizable task when it is necessary to justify the relationship structure of a large number of factors. In addition, the quality and interpretation of the results of statistical analysis are predetermined by the nature of the statistical models used to obtain sample estimates of their parameters. Due to the complexity of multidimensional statistical models, general theoretical concepts are usually limited by the assumption that the sampled data does not contradict the normal multidimensional distribution law. This greatly simplifies multivariate statistical analysis and therefore it always leads to linear regression relationships, which corresponds to a trivial system of correlation relationships and is rarely observed in reality. The structure of each economic object is unique, therefore, it is proposed to refine it using a system of correlation matrices of various orders. It is shown that the generalization of large volumes of multidimensional sample data in the form of “portraits” of correlation matrices clearly represents the specific features of the object of study. Moreover, the empirical system of statistically significant relationships is transformed into the corresponding model of economic relationships. Prerequisites are being created for the practical use of universal systems analysis methods based on modern theoretical and software tools of information technologies

Statistical Analsysis to Evaluate Heavy Metal Pollution in the Air Obatained by Moss Technique in Hanoi and its Surrounding Region

2019 ◽  
Vol 29 (3SI) ◽  
pp. 411
Author(s):  
N. H. Quyet ◽  
Le Hong Khiem ◽  
V. D. Quan ◽  
T. T. T. My ◽  
M. V. Frontasieva ◽  
...  
Keyword(s):  
Heavy Metal ◽  
Statistical Analysis ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Principal Component ◽  
Multivariate Statistical ◽  
Five Factors ◽  
Heavy Metal Elements ◽  
Surrounding Areas ◽  
Potential Pollution

The aim of this paper was the application of statistical analysis including principal component analysis to evaluate heavy metal pollution obtained by moss technique in the air of Ha Noi and its surrounding areas and to evaluate potential pollution sources. The concentrations of 33 heavy metal elements in 27 samples of Barbula Indica moss in the investigated region collected in December of 2016 in the investigated area have been examined using multivariate statistical analysis. Five factors explaining 80% of the total variance were identified and their potential sources have been discussed.

Multivariate statistical analysis of elements content in snow cover in Blagoveshchensk

2018 ◽  
Vol 52 (2) ◽  
pp. 15
Author(s):  
V. I. Radomskaya ◽  
D. V. Yusupov ◽  
L. М. Pavlova ◽  
А. G. Sеrgееvа ◽  
N. А. Bоrоdinа ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Snow Cover ◽  
Multivariate Statistical Analysis ◽  
Multivariate Statistical

Multivariate Statistical Analysis Regarding the Formulation of Oxicam-Based Pharmaceutical Hydrogels

2017 ◽  
Vol 68 (4) ◽  
pp. 726-731
Author(s):  
Lenuta Maria Suta ◽  
Anca Tudor ◽  
Colette Roxana Sandulovici ◽  
Lavinia Stelea ◽  
Daniel Hadaruga ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Multivariate Statistical Analysis ◽  
Pharmaceutical Formulations ◽  
Analysis Data ◽  
Multivariate Statistical ◽  
Predictive Variables ◽  
Rapid Release ◽  
Computational Data ◽  
Experimental Protocols ◽  
Formulation Factors

In this paper, it was analysed the influence of formulation factors over obtaining oxicam hydrogels, using the statistical analysis. Data analysis and predictive modeling by multivariate regression offers a large number of possible explanatory/predictive variables. Therefore, variable selection and dimension reduction is a major task for multivariate statistical analysis, especially for multivariate regressions. The statistical analysis and computational data processing of responses obtained from different pharmaceutical formulations, via different experimental protocols, lead to the optimization of the formulation process. It was found that the most suitable pharmaceutical formulations based on oxicams with the possibility of rapid release contained cyclodextrin, in particular 2-hydroxypropyl-b-cyclodextrin.

Engagement Through the Diaspora Channel

2017 ◽  
Author(s):  
Michael S. Danielson
Keyword(s):  
Civil Society ◽  
Statistical Models ◽  
State Level ◽  
The State ◽  
Multivariate Statistical ◽  
Political Factors ◽  
Data Set ◽  
Level Data ◽  
Municipal Level

The first empirical task is to identify the characteristics of municipalities which US-based migrants have come together to support financially. Using a nationwide, municipal-level data set compiled by the author, the chapter estimates several multivariate statistical models to compare municipalities that did not benefit from the 3x1 Program for Migrants with those that did, and seeks to explain variation in the number and value of 3x1 projects. The analysis shows that migrants are more likely to contribute where migrant civil society has become more deeply institutionalized at the state level and in places with longer histories as migrant-sending places. Furthermore, the results suggest that political factors are at play, as projects have disproportionately benefited states and municipalities where the PAN had a stronger presence, with fewer occurring elsewhere.

scholarly journals Nuclear Magnetic Resonance Metabolomics with Double Pulsed-Field-Gradient Echo and Automatized Solvent Suppression Spectroscopy for Multivariate Data Matrix Applied in Novel Wine and Juice Discriminant Analysis

Molecules ◽  
2021 ◽  
Vol 26 (14) ◽  
pp. 4146
Author(s):  
José Enrique Herbert-Pucheta ◽  
José Daniel Lozada-Ramírez ◽  
Ana E. Ortega-Regules ◽  
Luis Ricardo Hernández ◽  
Cecilia Anaya de Parrodi
Keyword(s):  
Statistical Analysis ◽  
Discriminant Analysis ◽  
Field Gradient ◽  
Multivariate Statistical Analysis ◽  
Data Matrix ◽  
Cabernet Sauvignon ◽  
Gradient Echo ◽  
Multivariate Statistical ◽  
Orthogonal Projections ◽  
Pulsed Field

The quality of foods has led researchers to use various analytical methods to determine the amounts of principal food constituents; some of them are the NMR techniques with a multivariate statistical analysis (NMR-MSA). The present work introduces a set of NMR-MSA novelties. First, the use of a double pulsed-field-gradient echo (DPFGE) experiment with a refocusing band-selective uniform response pure-phase selective pulse for the selective excitation of a 5–10-ppm range of wine samples reveals novel broad 1H resonances. Second, an NMR-MSA foodomics approach to discriminate between wine samples produced from the same Cabernet Sauvignon variety fermented with different yeast strains proposed for large-scale alcohol reductions. Third a comparative study between a nonsupervised Principal Component Analysis (PCA), supervised standard partial (PLS-DA), and sparse (sPLS-DA) least squares discriminant analysis, as well as orthogonal projections to a latent structures discriminant analysis (OPLS-DA), for obtaining holistic fingerprints. The MSA discriminated between different Cabernet Sauvignon fermentation schemes and juice varieties (apple, apricot, and orange) or juice authentications (puree, nectar, concentrated, and commercial juice fruit drinks). The new pulse sequence DPFGE demonstrated an enhanced sensitivity in the aromatic zone of wine samples, allowing a better application of different unsupervised and supervised multivariate statistical analysis approaches.

scholarly journals Metabolomic-Based Comparison of Traditional and Industrial Doenjang Samples with Antioxidative Activities

Foods ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 1377
Author(s):  
Song-Hui Soung ◽  
Sunmin Lee ◽  
Seung-Hwa Lee ◽  
Hae-Jin Kim ◽  
Na-Rae Lee ◽  
...  
Keyword(s):  
Amino Acids ◽  
Statistical Analysis ◽  
Organic Acids ◽  
Biogenic Amines ◽  
Multivariate Statistical Analysis ◽  
Metabolite Profiling ◽  
New Products ◽  
Multivariate Statistical ◽  
Fermentation Processes

Numerous varieties of doenjang are manufactured by many food companies using different ingredients and fermentation processes, and thus, the qualities such as taste and flavor are very different. Therefore, in this study, we compared many products, specifically, 19 traditional doenjang (TD) and 17 industrial doenjang (ID). Subsequently, we performed non-targeted metabolite profiling, and multivariate statistical analysis to discover distinct metabolites in two types of doenjang. Amino acids, organic acids, isoflavone aglycones, non-DDMP (2,3-dihydro-2,5-dihydroxy-6-methyl-4H-pyran-4- one) soyasaponins, hydroxyisoflavones, and biogenic amines were relatively abundant in TD. On the contrary, contents of dipeptides, lysophospholipids, isoflavone glucosides and DDMP-conjugated soyasaponin, precursors of the above-mentioned metabolites, were comparatively higher in ID. We also observed relatively higher antioxidant, protease, and β-glucosidase activities in TD. Our results may provide valuable information on doenjang to consumers and manufacturers, which can be used while selecting and developing new products.

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