inverse distribution function
31Error function — Plot of the error function In mathematics, the error function (also called the Gauss error function) is a special function (non elementary) of sigmoid shape which occurs in probability, statistics and partial differential equations. It is defined …
32Degenerate distribution — Degenerate Probability mass function PMF for k0=0. The horizontal axis is the index i of ki. (Note that the function is only defined at integer indices. The connecting lines do not indicate continuity.) Cumulative distribution function …
33Noncentral F-distribution — In probability theory and statistics, the noncentral F distribution is a continuous probability distribution that is a generalization of the (ordinary) F distribution. It describes the distribution of the quotient (X/n1)/(Y/n2), where the… …
34Normal-scaled inverse gamma distribution — Normal scaled inverse gamma parameters: location (real) (real) (real) (real) support …
35Uniform distribution (discrete) — discrete uniform Probability mass function n = 5 where n = b − a + 1 Cumulative distribution function …
36Quantile function — See also quantile. In probability theory, a quantile function of a probability distribution is the inverse F −1 of its cumulative distribution function (cdf) F . Assuming a continuous and strictly monotonic distribution function, scriptstyle… …
37Dagum distribution — Probability density function Cumulative distribution function No image available parameters: p > 0 shape a > 0 shape …
38Scale-inverse-chi-square distribution — Probability distribution name =Scale inverse chi square type =density pdf cdf parameters = u > 0, sigma^2 > 0, support =x in (0, infty) pdf =frac{(sigma^2 u/2)^{ u/2{Gamma( u/2)} frac{expleft [ frac{ u sigma^2}{2 x} ight] }{x^{1+ u/2 cdf… …
39Nakagami distribution — Nakagami Probability density function Cumulative distribution function parameters: μ > = 0.5 shape (real) …
40Davis distribution — Probability density function No image available Cumulative distribution function No image available parameters: b > 0 scale n > 0 shape μ > 0 location support: x > μ …
