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PDF

PDF(distribution, value)

returns the probability density function of value.

PDF(distribution, {list} )

returns the probability density function of the values of list.

See:

PDF can be applied to the following distributions:

BernoulliDistribution, BinomialDistribution, DiscreteUniformDistribution, ErlangDistribution, ExponentialDistribution, FrechetDistribution, GammaDistribution, GeometricDistribution, GumbelDistribution, HypergeometricDistribution, LogNormalDistribution, NakagamiDistribution, NormalDistribution, PoissonDistribution, StudentTDistribution, WeibullDistribution

Examples

>> PDF(NormalDistribution(n, m))
1/(Sqrt(2)*E^((-n+#1)^2/(2*m^2))*m*Sqrt(Pi))&
>> PDF(GumbelDistribution(n, m),k)
E^(-E^((k-n)/m)+(k-n)/m)/m
>> Table(PDF(NormalDistribution( ), x), {m, {-1, 1, 2}},{x, {-1, 1, 2}})//N
{{0.24197,0.24197,0.05399},{0.24197,0.24197,0.05399},{0.24197,0.24197,0.05399}}

CDF, InverseCDF

Implementation status

  • ✅ - full supported

Github