JointGaussianSqrtPrec

class cuqi.distribution.JointGaussianSqrtPrec(means=None, sqrtprecs=None, is_symmetric=True, **kwargs)

Joint Gaussian probability distribution defined by means and sqrt of precision matricies of independent Gaussians. Generates instance of cuqi.distribution.JointGaussianSqrtPrec.

Parameters:

• means (List of means for each Gaussian distribution.)

• sqrtprecs (List of sqrt precision matricies for each Gaussian distribution.)

__init__(means=None, sqrtprecs=None, is_symmetric=True, **kwargs)

Initialize the core properties of the distribution.

Parameters:

• name (str, default None) – Name of distribution.

• geometry (Geometry, default _DefaultGeometry (or None)) – Geometry of distribution.

• is_symmetric (bool, default None) – Indicator if distribution is symmetric.

Methods

__init__([means, sqrtprecs, is_symmetric])	Initialize the core properties of the distribution.
disable_FD()	Disable finite difference approximation for logd gradient.
enable_FD([epsilon])	Enable finite difference approximation for logd gradient.
get_conditioning_variables()	Return the conditioning variables of this distribution (if any).
get_mutable_variables()	Return any public variable that is mutable (attribute or property) except those in the ignore_vars list
get_parameter_names()	Returns the names of the parameters that the density can be evaluated at or conditioned on.
gradient(*args, **kwargs)	Returns the gradient of the log density at x.
logd(*args, **kwargs)	Evaluate the un-normalized log density function of the distribution.
logpdf(x)	Evaluate the log probability density function of the distribution.
pdf(x)	Evaluate the log probability density function of the distribution.
sample([N])	Sample from the distribution.
to_likelihood(data)	Convert conditional distribution to a likelihood function given observed data

Attributes

FD_enabled	Returns True if finite difference approximation of the logd gradient is enabled.
FD_epsilon	Spacing for the finite difference approximation of the logd gradient.
dim	Return the dimension of the distribution based on the geometry.
geometry	Return the geometry of the distribution.
is_cond	Returns True if instance (self) is a conditional distribution.
name	Name of the random variable associated with the density.
sqrtprec	Returns the sqrt precision matrix of the joined gaussian in stacked form.
sqrtprecTimesMean	Returns the sqrt precision matrix times the mean of the distribution.