Probability Distribution Functions
Probability distribution functions (PDF) are sometimes known as probability densities. In the case of continuous distributions, the area under the curve of the PDF for each interval equals the probability for the random variable to fall within that interval. The PDFs are useful in calculating event probabilities, characteristic functions and moments of a distribution.
| Function | Distribution |
| StatsBetaPDF | Beta |
| StatsBinomialPDF | Binomial |
| StatsCauchyPDF | Cauchy |
| StatsChiPDF | Chi-squared |
| StatsDExpPDF | Double-exponential |
| StatsErlangPDF | Erlang |
| StatsErrorPDF | Error |
| StatsEValuePDF | Extreme-value (type I, Gumbel) |
| StatsExpPDF | Exponential |
| StatsFPDF | F |
| StatsGammaPDF | Gamma |
| StatsGeometricPDF | Geometric |
| StatsHyperGPDF | Hyper-geometric |
| StatsLogNormalPDF | Lognormal |
| StatsMaxwellPDF | Maxwell |
| StatsNBinomialPDF | Negative binomial |
| StatsNCChiPDF | Non-central Chi-squared |
| StatsNCFPDF | Non-central F |
| StatsNCTPDF | Non-central Student T |
| StatsNormalPDF | Normal (Gaussian) |
| StatsParetoPDF | Pareto |
| StatsPoissonPDF | Poisson |
| StatsPowerPDF | Power |
| StatsRayleighPDF | Rayleigh |
| StatsRectangularPDF | Uniform |
| StatsStudentPDF | Student T |
| StatsTriangularPDF | Triangular |
| StatsVonMisesPDF | von-Mises |
| StatsWaldPDF | Wald |
| StatsWeibullPDF | Weibull |
Last updated: Wednesday, December 6, 2006