BetaGeoBetaBinomRV

class pymc_marketing.clv.distributions.BetaGeoBetaBinomRV(name=None, ndim_supp=None, ndims_params=None, dtype=None, inplace=None)

Methods

BetaGeoBetaBinomRV.L_op(inputs, outputs, ...)	Construct a graph for the L-operator.
BetaGeoBetaBinomRV.R_op(inputs, eval_points)	Construct a graph for the R-operator.
BetaGeoBetaBinomRV.__init__([name, ...])	Create a random variable Op.
BetaGeoBetaBinomRV.add_tag_trace([user_line])	Add tag.trace to a node or variable.
BetaGeoBetaBinomRV.batch_ndim(node)
BetaGeoBetaBinomRV.do_constant_folding(...)	Determine whether or not constant folding should be performed for the given node.
BetaGeoBetaBinomRV.grad(inputs, outputs)	Construct a graph for the gradient with respect to each input variable.
BetaGeoBetaBinomRV.infer_shape(fgraph, node, ...)
BetaGeoBetaBinomRV.make_node(rng, size, ...)	Create a random variable node.
BetaGeoBetaBinomRV.make_py_thunk(node, ...)	Make a Python thunk.
BetaGeoBetaBinomRV.make_thunk(node, ...[, impl])	Create a thunk.
BetaGeoBetaBinomRV.perform(node, inputs, outputs)	Calculate the function on the inputs and put the variables in the output storage.
BetaGeoBetaBinomRV.prepare_node(node, ...)	Make any special modifications that the Op needs before doing Op.make_thunk().
BetaGeoBetaBinomRV.rng_fn(rng, alpha, beta, ...)	Sample a numeric random variate.

Attributes

default_output	An int that specifies which output Op.__call__() should return.
destroy_map	A dict that maps output indices to the input indices upon which they operate in-place.
dtype
itypes
name
ndim_supp
ndims_params
otypes
view_map	A dict that maps output indices to the input indices of which they are a view.