cond {marg} | R Documentation |
Performs approximate conditional inference.
cond(object, offset, ...)
object |
a fitted model object. Families supported are binomial and
Poisson with canonical link function (class glm ), and
regression-scale models (class rsm ).
|
offset |
the covariate occurring in the model formula whose coefficient
represents the parameter of interest. May be numerical or a
two-level factor. In case of a two-level factor, it must be
coded by contrasts and not appear as two dummy variables in the
model. Can also be a call to a mathematical function (such as
exp , sin , ...) or to a mathematical
operator (\^ , / , ...) applied to a
numerical variable. The call must always agree with the label
used to identify the corresponding parameter in the fitted model
object passed through the object argument. Beware that
the label includes the identity function I() if an
arithmetic operator was used. Other function types (e.g.
factor ) and interactions are not admitted.
|
... |
absorbs any additional arguments. See cond.glm
and cond.rsm for details.
|
This function is generic (see methods
); method
functions can be written to handle specific classes of data.
Classes which already have methods for this function include:
glm
and rsm
.
The returned value is an approximate conditional inference
object. Classes already supported are cond
and
marg
depending on whether the fitted model object passed
through the object
argument has class glm
or
rsm
. See cond.object
or
marg.object
for more details.
Brazzale, A. R. (2000) Practical Small-Sample Parametric Inference. Ph.D. Thesis N. 2230, Department of Mathematics, Swiss Federal Institute of Technology Lausanne. Chapter 6.
cond.glm
, cond.rsm
,
cond.object
, marg.object
## Urine Data ## Not run: data(urine) urine.glm <- glm(r ~ gravity + ph + osmo + cond + urea + log(calc), family = binomial, data = urine) ## ## function call as offset variable labels(coef(urine.glm)) cond(urine.glm, log(calc)) ## ## large estimate of regression coefficient urine.glm <- glm(r ~ gravity + ph + osmo + cond + urea + calc, family = binomial, data = urine) coef(urine.glm) urine.glm <- glm(r ~ I(gravity * 100) + ph + osmo + cond + urea + calc, family = binomial, data = urine) coef(urine.glm) urine.cond <- cond(urine.glm, I(gravity * 100)) plot(urine.cond, which = 4) ## End(Not run) ## House Price Data data(houses) houses.rsm <- rsm(price ~ ., family = student(5), data = houses) ## ## parameter of interest: scale parameter houses.marg <- cond(houses.rsm, scale) plot(houses.marg, which = 2)