| glm.nb(MASS) | R Documentation |
A modification of the system function glm() to include estimation of the
additional parameter, theta, for a Negative Binomial generalized linear
model.
glm.nb(formula, ..., init.theta, link=log)
formula |
Model formula, as for glm().
|
... |
Any other arguments for the glm() function except family.
|
init.theta |
Optional initial value for the theta parameter. If omitted a moment estimator after an initial fit using a Poisson GLM is used. |
link |
The link function. Currently must be one of log, sqrt or identity.
|
An alternating iteration process is used. For given theta the GLM
is fitted using the same process as used by glm(). For fixed means
the theta parameter is estimated using score and information
iterations. The two are alternated until convergence of both. (The
number of alternations and the number of iterations when estimating
theta are controlled by the maxit parameter of glm.control.)
Setting trace > 0 traces the alternating iteration process. Setting
trace > 1 traces the glm fit, and setting trace > 2 traces the
estimation of theta.
A fitted model object of class negbin inheriting from glm and lm.
The object is like the output of glm but contains three additional
components, namely theta for the ML estimate of theta, SE.theta for
its approximate standard error (using observed rather than expected
information), and twologlik for twice the log-likelihood function.
glm, negative.binomial, anova.negbin, summary.negbin
data(quine) quine.nb1 <- glm.nb(Days ~ Sex/(Age + Eth*Lrn), data=quine) quine.nb2 <- update(quine.nb1, . ~ . + Sex:Age:Lrn) quine.nb3 <- update(quine.nb2, Days ~ .^4) anova(quine.nb1, quine.nb2, quine.nb3)