BoundedGaussianLinearPrior

class dysmalpy.parameters.BoundedGaussianLinearPrior(center=0, stddev=1.0)[source]

Methods Summary

`log_prior`(param, **kwargs)	Returns the log value of the prior given the parameter value
`prior_unit_transform`(param, u, **kwargs)	Map a uniform random variable drawn from [0.,1.] to the prior of interest
`sample_prior`(param[, N])	Returns a random sample of parameter values distributed according to the prior

Methods Documentation

log_prior(param, **kwargs)[source]: Returns the log value of the prior given the parameter value

prior_unit_transform(param, u, **kwargs)[source]: Map a uniform random variable drawn from [0.,1.] to the prior of interest

sample_prior(param, N=1, **kwargs)[source]: Returns a random sample of parameter values distributed according to the prior