Compute the signed log-likelihood ratio statistic (r_p) for a given value of the stress strength R = P(Y<X), that is the parameter of interest, under given parametric model assumptions.
rp(ydat, xdat, psi, distr = "exp")
data vector of the sample measurements from Y.
data vector of the sample measurements from X.
scalar for the parameter of interest. It is the value of R, treated as a parameter under the parametric model construction.
character string specifying the type of distribution assumed for Y and X.
Possible choices for
The two independent random variables Y and X with given distribution
distr are measurements of the diagnostic marker on the diseased
and non-diseased subjects, respectively.
For the relationship of the parameter of interest (R) and nuisance parameters with
the original parameters of
distr, look at the details in
Value of the signed log-likelihood ratio statistic r_p.
The r_p values can be also used for testing statistical hypotheses on the probability R.
Cortese G., Ventura L. (2013). Accurate higher-order likelihood inference on P(Y<X). Computational Statistics, 28:1035-1059.
Severini TA. (2000). Likelihood Methods in Statistics. Oxford University Press, New York.
Brazzale AR., Davison AC., Reid N. (2007). Applied Asymptotics. Case-Studies in Small Sample Statistics. Cambridge University Press, Cambridge.
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