RminusSReliability

class RminusSReliability(threshold=0.0, muR=4.0, sigmaR=1.0, muS=2.0, sigmaS=1.0)

Methods

computeBeta()	Return the beta of the reliability problem.
getEvent()	Return the event.
getName()	Return the name of the problem.
getProbability()	Return the probability.
toFullString()	Convert the object into a string, with full details.

__init__(threshold=0.0, muR=4.0, sigmaR=1.0, muS=2.0, sigmaS=1.0)

Create a R-S reliability problem.

The event is {g(X) < threshold} where

g(R, S) = R - S

We have R ~ Normal(muR, sigmaR) and S ~ Normal(muS, sigmaS).

Waarts (2000) uses muR = 7.0 and muS = 2.0 leading to beta = 3.54.

Parameters:

thresholdfloat

The threshold.

muRfloat

The mean of the R gaussian distribution.

sigmaRfloat

The standard deviation of the R gaussian distribution.

muSfloat

The mean of the S gaussian distribution.

sigmaSfloat

The standard deviation of the S gaussian distribution.

Examples

>>> import otbenchmark as otb
>>> problem = otb.RminusSReliability()

computeBeta()

Return the beta of the reliability problem.

This is the quantile of the probability of a standard gaussian distribution.

Parameters:

None.

Returns:

beta: float

The beta of the problem.

getEvent()

Return the event.

Parameters:

None.

Returns:

event: ot.ThresholdEvent

The event.

getName()

Return the name of the problem.

Parameters:

None.

Returns:

name: str

The name of the problem.

getProbability()

Return the probability.

Parameters:

None.

Returns:

probability: float

The probability of the event.

toFullString()

Convert the object into a string, with full details.

Parameters:

None.

Returns:

s: str

The string of the problem.