Multivariate statistical analysis and environmental isotopes of Amman/Wadi Sir (B2/A7) groundwater, Yarmouk River Basin, Jordan

2012 ◽  
Vol 27 (17) ◽  
pp. 2449-2461 ◽  
Author(s):  
Mutewekil Mamdouh Obeidat ◽  
Muheeb Awawdeh ◽  
Fahmi Abu Al-Rub
Keyword(s):  
Statistical Analysis ◽  
River Basin ◽  
Multivariate Statistical Analysis ◽  
Environmental Isotopes ◽  
Multivariate Statistical ◽  
Yarmouk River

scholarly journals Multivariate statistical analysis to support the minimum streamflow regionalization

2015 ◽  
Vol 35 (5) ◽  
pp. 838-851 ◽  
Author(s):  
Abrahão A. A. Elesbon ◽  
Demetrius D. da Silva ◽  
Gilberto C. Sediyama ◽  
Hugo A. S Guedes ◽  
Carlos A. A. S. Ribeiro ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Statistical Analysis ◽  
River Basin ◽  
Multivariate Statistical Analysis ◽  
Annual Rainfall ◽  
Morphometric Characteristics ◽  
Multivariate Statistical ◽  
Independent Variables ◽  
Homogeneous Regions ◽  
Doce River

ABSTRACT This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q7,10, Q90 and Q95). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall – Pa; total semiannual rainfall of the dry and of the rainy season – Pss and Psc; watershed drainage area – Ad; length of the main river – Lp; total length of the rivers – Lt; and average watershed slope – SL). The results of the principal component analysis pointed out that the variable SL was the least representative for the study, and so it was discarded. The most representative independent variables were Ad and Psc. The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin.

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.

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