Wiener Diffusion model test functions
Calculates test scores and further information for wdm
model objects.
## S3 method for class 'wdm' anova(object, ..., test="LRT") ## S3 method for class 'wdm' waldtest(object, ..., theta="delta", theta0=0)
object |
a wdm model object. |
test |
Statistical test to calculate, so far the only option is a likelihood-ratio test (LRT). |
... |
Further model objects or other arguments passed to methods. |
theta |
the name of the parameter to be tested. |
theta0 |
the value of the parameter under the null hypothesis. |
The anova.wdm function calls the specified test and calculates the
test statistics and other information for two or more nested
wdm model objects.
The waldtest.wdm function can be used to conduct a Wald test for a
single parameter.
# a random dataset
dat <- rbind(cbind(rwiener(100, 2,.3,.5,0), grp=factor("A", c("A","B"))),
cbind(rwiener(100,2,.3,.5,1), grp=factor("B", c("A","B"))))
# create nested wdm model objects (from specific to general)
wdm1 <- wdm(dat)
wdm2 <- wdm(dat,
alpha=coef(wdm1)[1], tau=coef(wdm1)[2], beta=coef(wdm1)[3],
xvar="grp")
wdm3 <- wdm(dat,
tau=coef(wdm1)[2],
xvar="grp")
# conduct LRT tests
anova1 <- anova(wdm1,wdm2,wdm3)
anova1
# waldtest
wt1 <- waldtest(wdm1, theta="delta", theta0=0)
wt1Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.