glm()
to include estimation of the
additional parameter,
theta
, for a
Negative Binomial generalized linear model.
glm.nb(formula, ..., init.theta, link = log)
glm()
.
glm()
function except
family
.
log
,
sqrt
or
identity
.
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.
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
.
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)