tests {RWiener} | R Documentation |
Wiener Diffusion model test functions
Description
Calculates test scores and further information for wdm
model objects.
Usage
## S3 method for class 'wdm'
anova(object, ..., test="LRT")
## S3 method for class 'wdm'
waldtest(object, ..., theta="delta", theta0=0)
Arguments
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. |
Details
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.
Examples
# 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)
wt1
[Package RWiener version 1.3-3 Index]