Inverse gamma distribution¶

This implementation uses the same parametrization as the SciPy implementation in scipy.stats.invgamma. loc and scale are the standard location and scale parameters, but typically discussions and implementations of the inverse gamma distribution do not include the location parameter that we include here and in SciPy (see, for example, the wikipedia article [1]).

mpsci.distributions.invgamma.cdf(x, a, loc=0, scale=1)¶: CDF for the inverse gamma distribution.

mpsci.distributions.invgamma.entropy(a, loc=0, scale=1)¶: Differential entropy of the inverse gamma distribution.

mpsci.distributions.invgamma.invcdf(p, a, loc=0, scale=1)¶: Inverse of the CDF for the inverse gamma distribution.

mpsci.distributions.invgamma.invsf(p, a, loc=0, scale=1)¶: Inverse of the survival function for the inverse gamma distribution.

mpsci.distributions.invgamma.kurtosis(a, loc=0, scale=1)¶: Excess kurtosis of the inverse gamma distribution.

mpsci.distributions.invgamma.logpdf(x, a, loc=0, scale=1)¶: Logarithm of the PDF for the inverse gamma distribution.

mpsci.distributions.invgamma.mean(a, loc=0, scale=1)¶

Mean of the inverse gamma distribution.

Returns nan if a <= 1.

mpsci.distributions.invgamma.mode(a, loc=0, scale=1)¶: Mode of the inverse gamma distribution.

mpsci.distributions.invgamma.noncentral_moment(n, a, loc=0, scale=1)¶

Noncentral moment of the inverse gamma distribution.

The value is also known as the raw moment.

mpsci.distributions.invgamma.pdf(x, a, loc=0, scale=1)¶: PDF for the inverse gamma distribution.

mpsci.distributions.invgamma.sf(x, a, loc=0, scale=1)¶: Survival function for the inverse gamma distribution.

mpsci.distributions.invgamma.skewness(a, loc=0, scale=1)¶: Skewness of the inverse gamma distribution.

mpsci.distributions.invgamma.support(a, loc=0, scale=1)¶: Support of the inverse gamma distribution.

mpsci.distributions.invgamma.var(a, loc=0, scale=1)¶

Variance of the inverse gamma distribution.

Returns nan if a <= 2.