wle.var.test(x, y, ratio = 1, alternative = c("two.sided", "less", "greater"),
conf.level = 0.95, x.root=1, y.root=1)
"wle.lm"
) or fitted normal model objects (inheriting from class "wle.normal"
).x
and y
."two.sided"
(default), "greater"
or "less"
. You
can specify just the initial letter."htest"
containing the following components:x
and y
."WF test to compare two variances"
.wle.normal
) or linear models (wle.lm
) x
and y
were fitted, is equal to ratio
.Agostinelli, C., (1998). Un approccio robusto alla verifica d'ipotesi basato sulla funzione di verosimiglianza pesata - Robust Testing Hypotheses via Weighted Likelihood function, submitted to {
Agostinelli, C., Markatou, M. (2001) Test of hypotheses based on the Weighted Likelihood Methodology, in print {
}
x <- rnorm(30,0,1) y <- rnorm(30,10,1)
res.x <- wle.normal(x,group=5) res.y <- wle.normal(y,group=5)
wle.var.test(res.x, res.y) # Do x and y have the same variance?
set.seed(1234)
x <- c(rnorm(30,0,1),rnorm(10,10,1)) y <- c(rnorm(30,10,1),rnorm(10,0,5))
res.x <- wle.normal(x,group=5,num.sol=2) res.y <- wle.normal(y,group=5)
res.x wle.var.test(res.x, res.y, x.root=1) if (res.x$tot.sol>1) wle.var.test(res.x, res.y, x.root=2)