factor transformation
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2021 ◽  
Vol 28 ◽  
pp. 151-155
Author(s):  
O. I. Blinkova

Aim. The aim of the study was to identify and systematize methodological problems in the diagnosis of anthropogenic transformation of forest ecosystem. Methods. Theoretical methods of system-structural, retrospective analysis, interdisciplinary, ecosystem approaches, special methods of forestry, synecology, ornithology and mycology. Results. Changes in functional indicators and parameters of communities were recorded depending on the genesis of the anthropogenic factor, pattern, intensity and time-scale of its impact and reproducibility of ecosystems. These changes were established in the presence of close correlation between the most sensitive structural and functional components (grass layer, leaf-litter, surface of soil, stand) and preserving the integrity of consorted links.  Conclusions. A conceptual model for diagnostic human transformation of forest ecosystems for various functional according to the state and development of consorted links of producers, consumers, reducers (for example, plants, fungi, birds) through qualitative and quantitative parameters of relevant diversity structures and principles of its application was proposed. Keywords: ecosystem, communities, anthropogenic factor, transformation, biodiversity, consorted links.


2020 ◽  
Vol 1 (2) ◽  
pp. 45
Author(s):  
Himayati Himayati ◽  
Ni Wayan Switrayni ◽  
Desy Komalasari ◽  
Nurul Fitriyani

Factor analysis is a multivariate statistical method that tries to explain the relationship between a number of independent variables by grouping these variables into factors. With this grouping, the existing variables will be easier to interpret. In increasing the power of factor interpretation, a matrix loading factor transformation must be performed. The transformation can be done by choosing the method that is in orthogonal rotation, the varimax or quartimax or equamax method. In order to find out which rotation techniques is the most appropriate, the minimum square distance values () generated from the procrustes method used. In this study three data were used from the results of the questionnaire, for data I obtain the value of the minimum distance squared with a varimax rotation that is  with ; for data II obtain the value of the minimum distance squared with a quartimax rotation that is  with ; for data III obtain the value of the minimum distance squared with a varimax rotation that is  with .


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