Wrapper around modeling function to make them behave enough alike that Wald tests and Likelihood ratio are easy to do.
To implement a new type of zero-inflated model, extend this class.
Depending on how different the method is, you will definitely need to override the fit
method, and possibly the model.matrix
, model.matrix<-
, update
, coef
, vcov
, and logLik
methods.
# S4 method for LMlike summary(object) # S4 method for LMlike update(object, formula., design, ...) # S4 method for LMlike,CoefficientHypothesis waldTest(object, hypothesis) # S4 method for LMlike,matrix waldTest(object, hypothesis) # S4 method for LMlike,character lrTest(object, hypothesis) # S4 method for LMlike,CoefficientHypothesis lrTest(object, hypothesis) # S4 method for LMlike,Hypothesis lrTest(object, hypothesis) # S4 method for LMlike,matrix lrTest(object, hypothesis) # S4 method for GLMlike logLik(object)
LMlike
formula
data.frame
model.matrix
CoefficientHypothesis
, Hypothesis
or contrast matrix
.see section "Methods (by generic)"
summary
: Print a summary of the coefficients in each component.
update
: update the formula or design from which the model.matrix
is constructed
waldTest
: Wald test dropping single term specified by CoefficientHypothesis
hypothesis
waldTest
: Wald test of contrast specified by contrast matrix hypothesis
lrTest
: Likelihood ratio test dropping entire term specified by character
hypothesis
naming a term in the symbolic formula.
lrTest
: Likelihood ratio test dropping single term specified by CoefficientHypothesis
hypothesis
lrTest
: Likelihood ratio test dropping single term specified by Hypothesis
hypothesis
lrTest
: Likelihood ratio test dropping single term specified by contrast matrix hypothesis
logLik
: return the log-likelihood of a fitted model
logical
with components "C" and "D", TRUE if the respective component has convergedformula
for the regressionlist
s giving arguments that will be passed to the fitter (such as convergence criteria or case weights)coef
lrTest
waldTest
vcov
logLik