The
cumulative distribution function (CDF) is given by
Similarly, to describe their joint distribution, we can use corresponding 2D
cumulative distribution function (cdf)
The
cumulative distribution function for the normal distribution is given as follows:
Let us now show the relationship between this function and other standard special functions (integral of error function) [4] as error function and
cumulative distribution function for normal distribution in the context of its use.
The
cumulative distribution function, moment, and stochastic representation will be presented when they correspond to the cases at hand.
For the analysis of the degree distribution, a common approach is to plot the complementary
cumulative distribution function P(k), which represents the fraction of nodes with degrees greater than or equal to k in the entire network.
The
cumulative distribution function of nonparametric probabilities of non-correlation with sex (Figure 4a) shows a very strong profile, affecting more than 30% of the peaks.
We reject [H.sub.0] if |z|>[z.sub.[alpha]/2], where [z.sub.[alpha]/2] denotes the upper [alpha]/2 quantile of the standard normal distribution, i.e., [PHI]([z.sub.[alpha]/2]) = 1- [alpha]/2, with [PHI] denoting the
cumulative distribution function of the standard normal distribution.
Probability distribution value can be calculated using
cumulative distribution function (CDF) and probability density function (PDF) of the captured image, whose values are achieved by brightness distribution of the captured image.