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Nowadays spatio-temporal analysis cannot be adequately faced without considering important issues, such as: (a) modeling the spatio-temporal random field from which data might be reasonably derived, (b) choosing suitable covariance models which describe the spatio-temporal correlation of the variables of interest, (c) using adequate software packages which tackle different inferential problems.
The correlation of the variables is analysed using linear regression yielding Pearson's correlation coefficients.
Due to some correlation of the variables especially between household size and the dummy for children, we tested the model in several specifications.
However, cross sectional dependence or cross sectional correlation of the variables is a fact that should be detected for the variables to decide which panel unit root test would be applied.
Based on the equation, where n is the number of samples (13 data sets) and r the correlation, the probability that both variables (AUC performance gain and flexibility of query compounds) result in such a correlation if there is no true correlation of the variables (ρ = 0.0) is 0.0277.
The graph shows correlation of the variables (P f and P f f are derived from presence and absence of the points), but it also shows how the ratio of P f and P f f changes for each height and zone.
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Spatial autocorrelation is the correlation of the variable with itself through space.
For each of four continuous variables (age, length of time with KPMAS, number of monthly encounters and baseline performance) we assessed the Pearson correlation of the variable with the outcome variables.
Weighted correlation network methods allow one to define a continuous measure of module membership for each variable in each module as the correlation of the variable profile with the module eigengene (Methods).
Based on the correlations of the variables of the mathematical model and analysis of the interaction between these variables, eleven independent variables were found.
When applied to the word sense and verb subcategorization frame determination tasks, the model learns sharp joint probability distributions which correspond to linguistic intuitions about the correlations of the variables.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com