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By representing the capacity and the demand as uniform random variables, an analytic solution is obtained for the probability distribution of the factor of safety and its probability density and cumulative distribution functions.
Figure 6 presents a spatial distribution of the factor coefficients along the river.
The spatial distribution of the factor scores of the element associations and their relationship with the geology are shown in Fig. 3a c.
First, a value is sampled from the posterior conditional distribution (or full conditional) of the latent underlying variables, then from the posterior conditional distribution of the factor loadings and so forth.
If the distribution of the factor within groups is uniform and so the cdf is linear, this reduces to Σ i ≠ j Σ k N ik ( a k + b k μ k j ) − c j.
8Instead of thinking of the distribution of the factor within a city, this can be interpreted as saying for example that net (and gross) migration from a city ranked three or lower into the top city is the total factor gain from the lower rank city achieving the mean factor of the top city.
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The spatial distribution of the factors score have been plotted using Map INFO professional 8.5 software.
Fig. 8 Testing the model by plotting observation vs. prediction Fig. 9 Distribution of the factors.
In any location i there is a distribution of the factors f defined by the cdf G i (f) with associated density g i (f).
Distribution of the factors is in accordance with the conclusions derived from the statistics described earlier.
After the factor analysis, we tested the normality of the distribution of the factors and decided to conserve the loading factors in the further analysis.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com