joint_probability

joint_probability(
    p,
    dependency='independent',
    indicators=None,
    correlation=None,
)

Joint probability of multiple events.

Mirrors the C# Probability.JointProbability. The plain form dispatches on a dependency assumption alone ("independent" multiplies, "positive" takes the minimum, "negative" clamps the excess of the sum over 1). Passing indicators (a 0/1 flag per component, selecting which components participate) switches to the indicator-aware form; passing correlation too routes dependency="correlation" through Haden Smith’s modification of Pandey’s Product-of-Conditional-Marginals method (HPCM).

Parameters

Name	Type	Description	Default
p	array_like	Marginal probabilities.	required
dependency	('independent', 'positive', 'negative', 'correlation')	"correlation" requires both indicators and correlation – the underlying C# method itself returns nan for that combination rather than raising an error, but this wrapper rejects it up front and names the missing argument(s), rather than handing back a silent nan.	"independent"
indicators	array_like	0/1 vector, the same length as p.	None
correlation	array_like	len(p) by len(p) correlation matrix; requires indicators.	None

Returns

Name	Type	Description
	float

Examples

>>> from corehydropy import joint_probability
>>> joint_probability([0.5, 0.5])
0.25
>>> joint_probability([0.5, 0.5], dependency="positive")
0.5