AssuranceResult#

class causalpy.checks.placebo_in_time.AssuranceResult[source]#

Bayesian operating characteristics from design-level simulation.

true_positive_rate#

P(decide “positive” | alternative true). This is the assurance.

Type:: float

false_positive_rate#

P(decide “positive” | null true).

Type:: float

true_negative_rate#

P(decide “null” | null true).

Type:: float

false_negative_rate#

P(decide “null” | alternative true).

Type:: float

null_indeterminate_rate#

P(decide “indeterminate” | null true).

Type:: float

alt_indeterminate_rate#

P(decide “indeterminate” | alternative true).

Type:: float

null_decisions#

Raw decision strings under the null scenario.

Type:: np.ndarray

alt_decisions#

Raw decision strings under the alternative scenario.

Type:: np.ndarray

Methods

AssuranceResult.__init__(true_positive_rate, ...)

Attributes

`true_positive_rate`
`false_positive_rate`
`true_negative_rate`
`false_negative_rate`
`null_indeterminate_rate`
`alt_indeterminate_rate`
`null_decisions`
`alt_decisions`

__init__(true_positive_rate, false_positive_rate, true_negative_rate, false_negative_rate, null_indeterminate_rate, alt_indeterminate_rate, null_decisions, alt_decisions)#

Parameters:

true_positive_rate (float)
false_positive_rate (float)
true_negative_rate (float)
false_negative_rate (float)
null_indeterminate_rate (float)
alt_indeterminate_rate (float)
null_decisions (ndarray)
alt_decisions (ndarray)

Return type:

None

classmethod __new__(*args, **kwargs)#