# ProbYX-package: Inference on the stress-strength model R = P(Y<X) In ProbYX: Inference for the Stress-Strength Model R = P(Y<X)

## Description

Compute confidence intervals and point estimates for R, under parametric model assumptions for Y and X. Y and X are two independent continuous random variables from two different populations.

## Details

 Package: ProbYX Type: Package Version: 1.1 Date: 2012-03-20 License: GPL-2 LazyLoad: yes

The package can be used for computing accurate confidence intervals and point estimates for the stress-strength (reliability) model R = P(Y<X); maximum likelihood estimates, Wald statistic, signed log-likelihood ratio statistic and its modified version ca be computed.
The main function is Prob, which evaluates confidence intervals and point estimates under different approaches and parametric assumptions.

## Author(s)

Giuliana Cortese

Maintainer: Giuliana Cortese <[email protected]>

## References

Cortese G., Ventura L. (2013). Accurate higher-order likelihood inference on P(Y<X). Computational Statistics, 28:1035-1059.

Kotz S, Lumelskii Y, Pensky M. (2003). The Stress-Strength Model and its Generalizations. Theory and Applications. World Scientific, Singapore.

## Examples

 1 2 3 4 5 6 7 8 9  # data from the first population Y <- rnorm(15, mean=5, sd=1) # data from the second population X <- rnorm(10, mean=7, sd=1.5) level <- 0.01 # \eqn{\alpha} level # estimate and confidence interval under the assumption of two # normal variables with different variances. Prob(Y, X, "norm_DV", "RPstar", level) # method has to be set equal to "RPstar". 

ProbYX documentation built on May 30, 2017, 8:12 a.m.