glimML-class {aod} | R Documentation |
Representation of Models of Formal Class "glimML"
Description
Representation of models of formal class "glimML" fitted by maximum-likelihood method.
Objects from the Class
Objects can be created by calls of the form new("glimML", ...)
or,
more commonly, via the functions betabin
or negbin
.
Slots
CALL
The call of the function.
link
The link function used to transform the mean: “logit”, “cloglog” or “log”.
method
The type of fitted model: “BB” for beta-binomial and “NB” for negative-binomial models.
formula
The formula used to model the mean.
random
The formula used to model the overdispersion parameter
.
data
Data set to which model was fitted. Different from the original data in case of missing value(s).
param
The vector of the ML estimated parameters
and
.
varparam
The variance-covariance matrix of the ML estimated parameters
and
.
fixed.param
The vector of the ML estimated fixed-effect parameters
.
random.param
The vector of the ML estimated random-effect (correlation) parameters
.
logL
The log-likelihood of the fitted model.
logL.max
The log-likelihood of the maximal model (data).
dev
The deviance of the model, i.e.,
- 2 * (logL - logL.max)
.df.residual
The residual degrees of freedom of the fitted model.
nbpar
The number of estimated parameters, i.e., nbpar = total number of parameters - number of fixed parameters. See argument
fixpar
inbetabin
ornegbin
.iterations
The number of iterations performed in
optim
.code
An integer (returned by
optim
) indicating why the optimization process terminated.- 1
Relative gradient is close to 0, current iterate is probably solution.
- 2
Successive iterates within tolerance, current iterate is probably solution.
- 3
Last global step failed to locate a point lower than estimate. Either estimate is an approximate local minimum of the function or
steptol
is too small.- 4
Iteration limit exceeded.
- 5
Maximum step size
stepmax
exceeded 5 consecutive times. Either the function is unbounded below, becomes asymptotic to a finite value from above in some direction orstepmax
is too small.
msg
Message returned by
optim
.singular.hessian
Logical: true when fitting provided a singular hessian, indicating an overparamaterized model.
param.ini
The initial values provided to the ML algorithm.
na.action
A function defining the action taken when missing values are encountered.