Module dstats.distrib

Probability distribution CDFs, PDFs/PMFs, and a few inverse CDFs.

Functions

Name Description
betaCDF
betaCDFR
betaPDF
binomialCDF P(K <= k) where K is random variable.
binomialCDFR P(K >= k) where K is random variable.
binomialPMF
cauchyCDF
cauchyCDFR
cauchyPDF
chiSquareCDF χ,2 distribution function and its complement.
chiSquareCDFR
chiSquarePDF
dirichletPDF The Dirichlet probability density.
exponentialCDF
exponentialCDFR
exponentialPDF
fisherCDF The Fisher distribution, its complement, and inverse.
fisherCDFR The Fisher distribution, its complement, and inverse.
gammaCDF
gammaCDFR
gammaPDF
hyperExact
hypergeometricCDF P(X <= x), where X is random variable. Uses either direct summation, normal or binomial approximation depending on parameters.
hypergeometricCDFR P(X >= x), where X is random variable.
hypergeometricPMF
invBetaCDF
invBinomialCDF Returns the value of k for the given p-value, n and p. If p-value does not exactly map to a value of k, the value for which binomialCDF(k, n, p) is closest to pVal is used.
invCauchyCDF
invChiSquareCDFR Inverse of complemented χ, 2 distribution
invExponentialCDF
invFisherCDFR Inverse of complemented Fisher distribution
invGammaCDF This just calls invGammaCDFR w/ 1 - p b/c invGammaCDFR is more accurate, but this function is necessary for consistency.
invGammaCDFR
invLaplaceCDF
invNegBinomCDF
invNormalCDF Inverse of Normal distribution function
invPoissonCDF Returns the value of k for the given p-value and lambda. If p-val doesn't exactly map to a value of k, the k for which poissonCDF(k, lambda) is closest to pVal is used.
invStudentsTCDF Inverse of Student's t distribution
kolmDist
kolmogorovDistrib Kolmogorov distribution. Used in Kolmogorov-Smirnov testing.
laplaceCDF
laplaceCDFR
laplacePDF
logisticCDF
logNormalCDF
logNormalCDFR
logNormalPDF
negBinomCDF Negative binomial distribution.
negBinomCDFR Probability that k or more failures precede the nth success.
negBinomPMF
normalCDF P(X < x) for normal distribution where X is random var.
normalCDFR P(X > x) for normal distribution where X is random var.
normalPDF
normApproxHyper
parametrize Takes a distribution function (CDF or PDF/PMF) as a template argument, and parameters as function arguments in the order that they appear in the function declaration and returns a delegate that binds the supplied parameters to the distribution function. Assumes the non-parameter argument is the first argument to the distribution function.
paramFunctor Takes a distribution function (CDF or PDF/PMF) as a template argument, and parameters as function arguments in the order that they appear in the function declaration and returns a functor that binds the supplied parameters to the distribution function. Assumes the non-parameter argument is the first argument to the distribution function.
poissonCDF P(K <= k) where K is r.v.
poissonCDFR P(K >= k) where K is r.v.
poissonPMF
rayleighCDF
studentsTCDF
studentsTCDFR
studentsTPDF
uniformCDF
uniformCDFR
uniformPDF
waldCDF
weibullCDF
weibullCDFR
weibullPDF

Structs

Name Description
ParamFunctor

Enum values

Name Type Description
POISSON_NORMAL
SQ2PI

Aliases

Name Type Description
chiSqrCDF
chiSqrCDFR
erf
erfc
invChiSqCDFR

Authors

David Simcha, Don Clugston

Copyright

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