Statistics: cdf

### Function Reference: `cdf`

statistics: p = cdf (name, x, A)
statistics: p = cdf (name, x, A, B)
statistics: p = cdf (name, x, A, B, C)
statistics: p = cdf (…, `"upper"`)

Return the CDF of a univariate distribution evaluated at x.

`cdf` is a wrapper for the univariate cumulative distribution functions available in the statistics package. See the corresponding functions’ help to learn the signification of the parameters after x.

`p = cdf (name, x, A)` returns the CDF for the one-parameter distribution family specified by name and the distribution parameter A, evaluated at the values in x.

`p = cdf (name, x, A, B)` returns the CDF for the two-parameter distribution family specified by name and the distribution parameters A and B, evaluated at the values in x.

`p = cdf (name, x, A, B, C)` returns the CDF for the three-parameter distribution family specified by name and the distribution parameters A, B, and C, evaluated at the values in x.

`p = cdf (…, `"upper"`)` returns the complement of the CDF using an algorithm that more accurately computes the extreme upper-tail probabilities. `"upper"` can follow any of the input arguments in the previous syntaxes.

name must be a char string of the name or the abbreviation of the desired cumulative distribution function as listed in the followng table. The last column shows the number of required parameters that should be parsed after x to the desired CDF. The optional input argument `"upper"` does not count in the required number of parameters.

Distribution Name |  | Abbreviation |  | Input Parameters
--- | --- | --- | --- | ---
`"Beta"` |  | `"beta"` |  | 2
`"Binomial"` |  | `"bino"` |  | 2
`"Birnbaum-Saunders"` |  | `"bisa"` |  | 2
`"Burr"` |  | `"burr"` |  | 3
`"Cauchy"` |  | `"cauchy"` |  | 2
`"Chi-squared"` |  | `"chi2"` |  | 1
`"Extreme Value"` |  | `"ev"` |  | 2
`"Exponential"` |  | `"exp"` |  | 1
`"F-Distribution"` |  | `"f"` |  | 2
`"Gamma"` |  | `"gam"` |  | 2
`"Geometric"` |  | `"geo"` |  | 1
`"Generalized Extreme Value"` |  | `"gev"` |  | 3
`"Generalized Pareto"` |  | `"gp"` |  | 3
`"Gumbel"` |  | `"gumbel"` |  | 2
`"Half-normal"` |  | `"hn"` |  | 2
`"Hypergeometric"` |  | `"hyge"` |  | 3
`"Inverse Gaussian"` |  | `"invg"` |  | 2
`"Laplace"` |  | `"laplace"` |  | 2
`"Logistic"` |  | `"logi"` |  | 2
`"Log-Logistic"` |  | `"logl"` |  | 2
`"Lognormal"` |  | `"logn"` |  | 2
`"Nakagami"` |  | `"naka"` |  | 2
`"Negative Binomial"` |  | `"nbin"` |  | 2
`"Noncentral F-Distribution"` |  | `"ncf"` |  | 3
`"Noncentral Student T"` |  | `"nct"` |  | 2
`"Noncentral Chi-Squared"` |  | `"ncx2"` |  | 2
`"Normal"` |  | `"norm"` |  | 2
`"Poisson"` |  | `"poiss"` |  | 1
`"Rayleigh"` |  | `"rayl"` |  | 1
`"Rician"` |  | `"rice"` |  | 2
`"Student T"` |  | `"t"` |  | 1
`"location-scale T"` |  | `"tls"` |  | 3
`"Triangular"` |  | `"tri"` |  | 3
`"Discrete Uniform"` |  | `"unid"` |  | 1
`"Uniform"` |  | `"unif"` |  | 2
`"Von Mises"` |  | `"vm"` |  | 2
`"Weibull"` |  | `"wbl"` |  | 2

See also: icdf, pdf, cdf, betacdf, binocdf, bisacdf, burrcdf, cauchycdf, chi2cdf, evcdf, expcdf, fcdf, gamcdf, geocdf, gevcdf, gpcdf, gumbelcdf, hncdf, hygecdf, invgcdf, laplacecdf, logicdf, loglcdf, logncdf, nakacdf, nbincdf, ncfcdf, nctcdf, ncx2cdf, normcdf, poisscdf, raylcdf, ricecdf, tcdf, tricdf, unidcdf, unifcdf, vmcdf, wblcdf

Source Code: cdf