BetaGeoBetaBinomRV#

class pymc_marketing.clv.distributions.BetaGeoBetaBinomRV(name=None, ndim_supp=None, ndims_params=None, dtype=None, inplace=None, signature=None)[source]#

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.dist_params`(node)	Return the node inpust corresponding to dist params
`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.inplace_on_inputs`(...)	Try to return a version of self that tries to inplace in as many as `allowed_inplace_inputs`.
`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.
`BetaGeoBetaBinomRV.rng_param`(node)	Return the node input corresponding to the rng
`BetaGeoBetaBinomRV.size_param`(node)	Return the node input corresponding to the size

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`
`otypes`
`signature`
`view_map`	A `dict` that maps output indices to the input indices of which they are a view.