Hydrogeochemistry and isotope compositions of multi-layered aquifer systems in the Recife Metropolitan Region, Pernambuco (NE Brazil): An integrated approach using multivariate statistical analyses

2021 ◽  
pp. 103323
Author(s):  
Thyego R. Silva ◽  
Teresa E. Leitão ◽  
Mariucha M.C. Lima ◽  
Tiago N. Martins ◽  
Manuel M. Oliveira ◽  
...  
Keyword(s):  
Integrated Approach ◽  
Statistical Analyses ◽  
Metropolitan Region ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Aquifer Systems

scholarly journals Principal components analysis of employment in Eastern Europe

2006 ◽  
Vol 53 (4) ◽  
pp. 427-437 ◽  
Author(s):  
Mirko Savic
Keyword(s):  
Eastern Europe ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Statistical Analyses ◽  
Multivariate Methods ◽  
Eastern European ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Full Picture ◽  
Components Analysis

For the last decade, the employment structure is one of the fastest changing areas of Eastern Europe. This paper explores the best methodology to compare the employment situations in the countries of this region. Multivariate statistical analyses are very reliable in portraying the full picture of the problem. Principal components analysis is one of the simplest multivariate methods. It can produce very useful information about Eastern European employment in a very easy and understandable way.

scholarly journals MICROMORPHOLOGICAL OBSERVATION OF EUCALYPTUS SEEDS, MULTIVARIATE STATISTICAL ANALYSES AND MODELING OF THEIR GERMINATION UNDER SALT STRESS AND OSMOTIC CONSTRAINT

CERNE ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 156-171
Author(s):  
KAOUTHER MECHERGUI ◽  
WAHBI JAOUADI ◽  
SOUHEILA NAGHMOUCHI ◽  
MOODI ALSUBEIE ◽  
Mohamed Larbi Khouja
Keyword(s):  
Salt Stress ◽  
Statistical Analyses ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical

Wood anatomical variability in Early Permian ‘araucarioids’

IAWA Journal ◽  
2014 ◽  
Vol 35 (3) ◽  
pp. 307-331 ◽  
Author(s):  
Menno Booi ◽  
Isabel M. van Waveren ◽  
Johanna H.A. van Konijnenburg-van Cittert
Keyword(s):  
Principal Component Analysis ◽  
Wood Species ◽  
Principal Component ◽  
Statistical Analyses ◽  
Late Paleozoic ◽  
Individual Species ◽  
Early Permian ◽  
Multivariate Statistical Analyses ◽  
Multivariate Statistical ◽  
Anatomical Analysis

Although araucarioid wood is poor in diagnostic characters, well in excess of 200 Late Paleozoic species have been described. This study presents a largescale anatomical analysis of this wood type based on the fossil wood collections from the Early Permian Mengkarang Formation of Sumatra, Indonesia. Principal Component Analysis visualisation, in conjunction with uni- and multivariate statistical analyses clearly show the wood from the Mengkarang Formation to be a contiguous micromorphological unit in which no individual species can be distinguished. Pycnoxylic wood species described previously from this collection or other collections from the Mengkarang Formation fall within the larger variability described here. Based on comparison with wood from modern-day Araucariaceae, the Early Permian specimens can be differentiated from extant (but unrelated) “araucarioids” by a few (continuous) characters.

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