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Cumulative probability function.
Fragility curve is developed based on the probabilistic hazard level, cumulative probability function and classification damage-states.
The cumulative probability function of δ p (Eq. 2) used in our application allows researchers to explicitly test hypotheses about group differences in the proportion of examinees affected by PD via the estimates of π Ig (Eq. 3).
In order to solve this problem, Cao and Stokes (2008) proposed a cumulative probability function of switching points, which was also employed by Jin and Wang (2014) in their mixture PD model.
Cao and Stokes (2008) assume that the cumulative probability function of δ p depends on a shape parameter ω > 0, so that Pleft( {delta_{p} le i |G = g} right) = frac{{i^{{upomega_{text{g}} }} }}{{(I - 1)^{{upomega_{text{g}} }} }},quad {text{for}};i < I. (2).
Thus, under the assumption of large number of transmitters and for any action profile p ∈ P ( b ), it follows that, ∀ s ∈ S, 1 K s ( p ) ∑ k ∈ K s ( p ) g k, s → K → ∞ ∫ 0 ∞ λ F̣ g s = Ω s, where F g s is the cumulative probability function associated with the channel gains over dimension s.
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Figure 6 Overall throughput cumulative probability functions in different schemes.
Figure 5 Cumulative probability functions of orthogonality defects (in logarithm) from 10, 000 random examples.
Figure 7 Average overall throughput cumulative probability functions in different areas in the location-based algorithm.
Figure 8 Cumulative probability functions of minimum angles (in degrees) from 10, 000 random examples.
Together with the original problems, we have plotted the cumulative probability functions (cdf) of the orthogonality defects in Figure 5.
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