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Critical crystallographic ratios and transformed variables with good correlations to average ring size were calculated.
To satisfy assumptions of linear regression, models originally utilized transformed variables.
Determining appropriate survey weights is independent of the flexible modeling strategy employed with the transformed variables.
It is shown that these transformed variables can be directly generalized to the dynamic problem considered here.
The transformed variables were then screened for multicollinearity.
The PIC analysis was conducted using the computer program Compare 4.6b on the transformed variables [70].
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The variable selection was repeated for log-transformed variables and square root transformed response variable.
Factor analyses were conducted on data with reflect and inverse transformations, but reliability of non-transformed variables is reported.
Analysis was conducted using Laplace-transformed variables and did not require time-domain solutions.
The use of biplots of clr-transformed variables allows discrimination of two different groups of shales.
All correlations were conducted using these log-transformed variables, where applicable.
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