cumulative distribution function


Also found in: Acronyms, Encyclopedia, Wikipedia.

cumulative distribution function

n
(Statistics) statistics a function defined on the sample space of a distribution and taking as its value at each point the probability that the random variable has that value or less. The function F(x) = P(Xx) where X is the random variable, which is the sum or integral of the probability density function of the distribution. Sometimes shortened to: distribution function
References in periodicals archive ?
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.
alpha]/2]) = 1- [alpha]/2, with [PHI] denoting the cumulative distribution function of the standard normal distribution.
In order to test if the Pareto power law distribution fits the data well, the complementary cumulative distribution function (C-CDF), Eq.
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.
It also includes sophisticated software features, such as the complementary cumulative distribution function (CCDF), automatic current, and power profiling.
Different properties were used to find out the cumulative distribution function, probability density function (PDF), hazard function, Reverse Hazard and survival functions.
The cumulative distribution function F(x) is shown in Figure 7 (b) and it is the integral of the probability density function f(t) as given in Equation 9.
cdf(v)--is the cumulative distribution function calculated in step 2
Consequently, we first discuss the mean, the variance, probability density function (PDF), and cumulative distribution function (CDF) about the energy of the compressed signal and the energy of the compressed noise.
A cumulative distribution function F(t) can be used to describe the probability of observing time T less than or equal to a time t.
Hence [mathematical expression not reproducible] by the monotone property of the cumulative distribution function.
in which f denotes the density probability function, F is the cumulative distribution function of the random variable T and [theta] = (b, c) is the vector of parameters.

Full browser ?