...
The probabilistic feature provides arbitrary functions to work with discrete and continuous random variables in a data stream and provides algebraic operator (+, *, -, /) to perform probabilistic addition, subtraction, multiplication, division, and exponentiation.
Int(
...
<ProbabilisticDouble x, Number a, Number b>|<Vector xyz, Vector a,
...
Vector b>)
Estimates the multivariate normal distribution probability with lower and upper integration limit.
as2DVector(
...
ProbabilisticDouble x, ProbabilisticDouble y)
Converts the two object into a 2D vector.
as3DVector(
...
ProbabilisticDouble x, ProbabilisticDouble y, ProbabilisticDouble z)
Similar to the as2DVector function, this function creates a 3D vector with the given objects.
Similarity(
...
ProbabilisticDouble p1, ProbabilisticDouble p2)
Calculates the Bhattacharyya distance between two distributions.
Code Block | ||||
---|---|---|---|---|
| ||||
SELECT similarity(as2DVector(x1,y1), as2DVector(x2,y2)) FROM stream |
Distance(
...
<ProbabilisticDouble p, Number x>|<Vector p, Vector x>)
Calculates the Mahalanobis distance between the distribution and the value. The value can be a scalar value or a vector.
Code Block | ||||
---|---|---|---|---|
| ||||
SELECT distance(as3DVector(x, y, z), [1.0;2.0;3.0]) FROM stream |
KL(<ProbabilisticDouble p1, ProbabilisticDouble p2>|<Vector p1, Vector p2>)
Calculates the Kullback-Leibler divergence of the two given probability distributions.
Code Block | ||||
---|---|---|---|---|
| ||||
SELECT kl(as3DVector(x, y, z), as3DVector(a, b, c)) FROM stream |
LogLikelihood(Vector points, ProbabilisticDouble p)
Calculates the log Likelihood between the given points and the probability distribution.
Code Block | ||||
---|---|---|---|---|
| ||||
SELECT loglikelihood([1.0;2.0;3.0], x) FROM stream |