wald | R Documentation |
Compute the Wald statistic for a given value of the stress-strength R = P(Y<X), that is the parameter of interest, under given parametric model assumptions.
wald(ydat, xdat, psi, distr = "exp")
ydat |
data vector of the sample measurements from Y. |
xdat |
data vector of the sample measurements from X. |
psi |
scalar for the parameter of interest. It is the value of the quantity R, treated as a parameter under the parametric model construction. |
distr |
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 from two different populations.
For the relationship of the parameter of interest (R) and nuisance parameters with
the original parameters of distr
, look at the details in loglik
.
Wald |
Value of the Wald statistic for a given |
Jphat |
Observed profile Fisher information |
Values of the Wald statistic can be also used for testing statistical hypotheses on the probability R.
Giuliana Cortese
Cortese G., Ventura L. (2013). Accurate higher-order likelihood inference on P(Y<X). Computational Statistics, 28:1035-1059.
Brazzale AR., Davison AC., Reid N. (2007). Applied Asymptotics. Case-Studies in Small Sample Statistics. Cambridge University Press, Cambridge.
rp
, rpstar
, MLEs
, Prob
# 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) # value of Wald for \code{psi=0.9} wald(Y, X, 0.9,"norm_DV")
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