The inverse cumulative distribution functions return the values at which their respective CDFs attain a given level. This value is typically used in hypothesis testing as a critical value.

There are very few functions for which the inverse CDF can be written in closed form. In most situations the inverse is computed numerically from the CDF.

Function Distribution
StatsInvBetaCDF Beta
StatsInvBinomialCDF Binomial
StatsInvCauchyCDF Cauchy
StatsInvChiCDF Chi-squared
StatsInvCMSSDCDF C (mean square successive difference)
StatsInvDExpCDF Double-exponential
StatsInvEValueCDF Extreme-value (type I Gumble)
StatsInvExpCDF Exponential
StatsInvFCDF F
StatsInvFriedmanCDF Friedman
StatsInvGammaCDF Gamma
StatsInvGeometricCDF Geometric
StatsInvKuiperCDF Kuiper
StatsInvLogisticCDF Logistic
StatsInvLogNormalCDF Lognormal
StatsInvMaxwellCDF Maxwell
StatsInvMooreCDF Moore
StatsInvNBinomialCDF Negative-binomial
StatsInvNCFCDF Non-central F
StatsInvNormalCDF Normal (Gaussian)
StatsInvParetoCDF Pareto
StatsInvPoissonCDF Poisson
StatsInvPowerCDF Power
StatsInvQCDF Q
StatsInvQpCDF Modified Q
StatsInvRayleighCDF Rayleigh
StatsInvRectangularCDF Uniform
StatsInvSpearmanCDF Spearman rho
StatsInvStudentCDF Student-T
StatsInvTopDownCDF Top Down
StatsInvTriangularCDF Triangular
StatsInvUSquaredCDF Watson's U-squared
StatsInvVonMisesCDF von Mises
StatsInvWeibullCDF Weibull




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