Cumulative Distribution Functions (CDF)


Name Brief Example
Betacdf Computes beta cumulative distribution function at x, with parameters a and b.
Binocdf Computes the lower tail, upper tail and point probabilities in given value k, associated with a Binomial distribution using the corresponding parameters in n, p.
Bivarnormcdf Computes the lower tail probability for the bivariate Normal distribution.
Chi2cdf Computes the lower tail probability for the \chi^2 distribution with real degrees of freedom.
Cumul normal Evaluates the cumulative Normal distribution function P(x)=\frac 1{\sqrt{2\pi }}\int_{-\infty }^xe^{\frac{-u^2}2}du.
Cumul normal complem Evaluates an approximate value for the complement of the cumulative normal distribution function.
Erf The error function (or normal error integral).
Erfc The approximate value for the complement of the error function.
Erfcinv Return value of the inverse of the complementary error function for specified y.
Erfinv Return value of the inverse error function for specified y.
Fcdf Computes F cumulative distribution function at x, with parameters a and b, and lower tail.
Foldnormcdf Computes the lower tail probability for the Folded Normal distribution.
Gamcdf Computes the lower tail probability for the gamma distribution with real degrees of freedom, with parameters \alpha and \beta .
Hygecdf Computes the lower tail probabilities in given value , associated with a hypergeometric distribution using the corresponding parameters in ,nand .
Landaucdf Computes the cumulative density for the Landau distribution at x and with location parameter mu and scale parameter sigma.
Logncdf Computes the lower tail probability for the Lognormal cumulative distribution with parameters  \mu and \sigma.
Ncbetacdf Computes the cdf with the lower tail of the non-central beta distribution.
Ncchi2cdf Computes the probability associated with the lower tail of the non-central \chi^2 distribution.
Ncfcdf Computes the probability associated with the lower tail of the non-central \digamma or variance-ratio distribution.
Nctcdf Computes the lower tail probability for the non-central Student's t-distribution.
Normcdf Computes the lower tail probability for the normal cumulative distribution.
Poisscdf Computes the lower tail probabilities in given value k, associated with a Poisson distribution using the corresponding parameters in \lambda.
Prob Computes the Probability Density (for a normal distribution) integrated from -x to +x.
Srangecdf Computes the probability associated with the lower tail of the distribution of the Studentized range statistic.
Tcdf Computes the cumulative distribution function of Student's t-distribution.
Wblcdf computes the low tail Weibull cumulative distribution function for value X using the parameters A and B.