SSR: Computation of reliability of stress-strength models

In StressStrength: Computation and Estimation of Reliability of Stress-Strength Models

Description

For a stress-strength model, with independent r.v. X and Y representing the strength and the stress respectively, the function computes the reliability R=P(X>Y)

Usage

SSR(parx, pary, family = "normal")

Arguments

parx	parameters of X distribution (for the normal distribution, mean μ_x and standard deviation σ_x)
pary	parameters of Y distribution (for the normal distribution, mean μ_y and standard deviation σ_y)
family	family distribution for both X and Y (now, only "normal" available)

Details

The function computes R=P(X>Y) where X and Y are independent r.v. following the family distribution with distributional parameters parx and pary.

Value

R=P(X>Y). For normal distributions, R=Φ(d) with d=(μ_x-μ_y)/√{σ_x^2+σ_y^2}.

Author(s)

Alessandro Barbiero, Riccardo Inchingolo

References

Kotz S, Lumelskii Y, Pensky M (2003) The stress-strength model and its generalizations: theory and applications. World Scientific, Singapore

See Also

estSSR

Examples

# let X be a normal r.v. with mean 1 and sd 1;
# and Y a normal r.v. with mean 0 and sd 2
# X and Y independent
parx<-c(1, 1)
pary<-c(0, 2)
# reliability of the stress-strength model (X=strength, Y=stress)
SSR(parx,pary)
# changing the parameters of Y
pary<-c(1.5, 2)
# reliability of the stress-strength model (X=strength, Y=stress)
SSR(parx,pary)

Example output

[1] 0.6726396
[1] 0.4115316

StressStrength documentation built on May 2, 2019, 2:12 p.m.