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 \phi.
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 b and \phi.
varparam
- The variance-covariance matrix of the ML estimated parameters b and \phi.
fixed.param
- The vector of the ML estimated fixed-effect parameters b.
random.param
- The vector of the ML estimated random-effect (correlation) parameters \phi.
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
in betabin
or negbin
.
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 or stepmax
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.
[Package
aod version 1.1-31
Index]