| 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 1.1-29
Index]