Evaluations

fenbux.logpdf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Log probability density function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the logpdf at.	required

Examples:

>>> from fenbux import Normal, logpdf
>>> dist = Normal(0.0, 1.0)
>>> logpdf(dist, 0.0)
Array(-0.9189385, dtype=float32)

fenbux.pdf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Probability density function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the pdf at.	required

Examples:

>>> from fenbux import Normal, pdf
>>> dist = Normal(0.0, 1.0)
>>> pdf(dist, 0.0)
Array(0.3989423, dtype=float32)

fenbux.logcdf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Log cumulative distribution function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the logcdf at.	required

Examples:

>>> from fenbux import Normal
>>> dist = Normal(0.0, 1.0)
>>> logcdf(dist, 0.0)
Array(-0.6931472, dtype=float32)

fenbux.cdf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Cumulative distribution function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the cdf at.	required

Examples:

>>> from fenbux import Normal, cdf
>>> dist = Normal(0.0, 1.0)
>>> cdf(dist, 0.0)
Array(0.5, dtype=float32)

fenbux.quantile(dist: AbstractDistribution, p: ArrayLike) -> PyTree

Quantile function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
p	ArrayLike	Value to evaluate the quantile at.	required

Examples:

>>> from fenbux import Normal
>>> n = Normal(0.0, 1.0)
>>> quantile(n, 0.5)
Array(0., dtype=float32)

fenbux.sf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Survival function of the distribution

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the sf at.	required

Examples:

>>> from fenbux import Normal, sf
>>> dist = Normal(0.0, 1.0)
>>> sf(dist, 0.)
Array(0.5, dtype=float32)

fenbux.logsf(dist: AbstractDistribution, x: ArrayLike) -> PyTree

Log survival function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
x	ArrayLike	Value to evaluate the logsf at.	required

Examples:

>>> from fenbux import Normal
>>> dist = Normal(0.0, 1.0)
>>> logsf(dist, 0.0)
Array(-0.6931472, dtype=float32)

fenbux.mgf(dist: AbstractDistribution, t: ArrayLike) -> PyTree

Moment generating function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
t	ArrayLike	Value to evaluate the mgf at.	required

Examples:

>>> from fenbux import Normal, mgf
>>> dist = Normal(0.0, 1.0)
>>> mgf(dist, 0.5)
Array(1.1331484, dtype=float32)

fenbux.cf(dist: AbstractDistribution, t: ArrayLike) -> PyTree

Characteristic function

Parameters:

Name	Type	Description	Default
dist	AbstractDistribution	Distribution object.	required
t	ArrayLike	Value to evaluate the cf at.	required

Examples:

>>> from fenbux import Normal, cf
>>> dist = Normal(0.0, 1.0)
>>> cf(dist, 0.5)
Array(0.8824969+0.j, dtype=complex64)