Approximate Conditional Inference - Generic Function
Performs approximate conditional inference.
a fitted model object. Families supported are binomial and
Poisson with canonical link function (class
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
absorbs any additional arguments. See
This function is generic (see
functions can be written to handle specific classes of data.
Classes which already have methods for this function include:
The returned value is an approximate conditional inference
object. Classes already supported are
marg depending on whether the fitted model object passed
object argument has class
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.
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## Urine Data data(urine) urine.glm <- glm(r ~ gravity + ph + osmo + conduct + 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 + conduct + urea + calc, family = binomial, data = urine) coef(urine.glm) urine.glm <- glm(r ~ I(gravity * 100) + ph + osmo + conduct + urea + calc, family = binomial, data = urine) coef(urine.glm) urine.cond <- cond(urine.glm, I(gravity * 100)) plot(urine.cond, which = 4) ## House Price Data ## Not run: 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) ## End(Not run)
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