bilby.core.likelihood.AnalyticalMultidimensionalCovariantGaussian

class bilby.core.likelihood.AnalyticalMultidimensionalCovariantGaussian(mean, cov)

Bases: Likelihood

A multivariate Gaussian likelihood with known analytic solution.

Parameters:

mean: array_like

Array with the mean values of distribution

cov: array_like

The ndim*ndim covariance matrix

__init__(mean, cov)

Empty likelihood class to be subclassed by other likelihoods

__call__(*args, **kwargs)

Call self as a function.

Methods

__init__(mean, cov)	Empty likelihood class to be subclassed by other likelihoods
log_likelihood(parameters)
log_likelihood_ratio(parameters)	Difference between log likelihood and noise log likelihood
noise_log_likelihood()

Attributes

dim
marginalized_parameters
meta_data

log_likelihood(parameters)

Parameters:

parameters: dict

A dictionary of the parameter names and associated values

Returns:

float

log_likelihood_ratio(parameters)

Difference between log likelihood and noise log likelihood

Parameters:

parameters: dict

A dictionary of the parameter names and associated values

Returns:

float

noise_log_likelihood()

Returns:

float