- formula
A formula expression response ~ predictors
;
- id
A vector for identifying subjects/clusters.
- data
A data frame which stores the variables in formula
with id
variable.
- na.action
A function to remove missing values from the data. Only na.omit
is allowed here.
- family
A family
object: a list of functions and expressions for defining link
and
variance
functions. Families supported in PGEE
are binomial
, gaussian
, gamma
and
poisson
. The links
, which are not available in gee
, is not available here. The default family
is gaussian
.
- corstr
A character string, which specifies the correlation of correlation structure.
Structures supported in PGEE
are "AR-1"
,"exchangeable"
, "fixed"
, "independence"
,
"stat_M_dep"
,"non_stat_M_dep"
, and "unstructured"
. The default corstr
correlation is
"independence"
.
- Mv
If either "stat_M_dep"
, or "non_stat_M_dep"
is specified in corstr
, then this
assigns a numeric value for Mv
. Otherwise, the default value is NULL
.
- beta_int
User specified initial values for regression parameters. The default value is NULL
.
- R
If corstr = "fixed"
is specified, then R
is a square matrix of dimension maximum cluster
size containing the user specified correlation. Otherwise, the default value is NULL
.
- scale.fix
A logical variable; if true, the scale parameter is fixed at the value of scale.value
.
The default value is TRUE
.
- scale.value
If scale.fix = TRUE
, this assigns a numeric value to which the scale parameter should be
fixed. The default value is 1.
- lambda
A numerical value for the penalization parameter of the scad function, which is estimated via
cross-validation.
- pindex
An index vector showing the parameters which are not subject to penalization. The default value
is NULL
. However, in case of a model with intercept, the intercept parameter should be never penalized.
- eps
A numerical value for the epsilon used in minorization-maximization algorithm. The default value is
10^-6
.
- maxiter
The number of iterations that is used in the estimation algorithm. The default value is 25
.
- tol
The tolerance level that is used in the estimation algorithm. The default value is 10^-3
.
- silent
A logical variable; if false, the regression parameter estimates at each iteration are
printed. The default value is TRUE
.