confint.lmgce {GCEstim} | R Documentation |
Confidence Intervals for lmgce
Model Parameters and
Normalized Entropy
Description
Computes confidence intervals for one or more parameters or Normalized Entropy
in a lmgce
fitted model.
Usage
## S3 method for class 'lmgce'
confint(
object,
parm,
level = 0.95,
which = c("estimates", "NormEnt"),
method = {
if (which == "estimates") {
c("z", "percentile", "basic")
}
else {
c("percentile", "basic")
}
},
boot.B = ifelse(object$boot.B == 0, 100, object$boot.B),
boot.method = object$boot.method,
...
)
Arguments
object |
Fitted |
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. |
level |
the confidence level required. The default is
|
which |
One of |
method |
method used to compute the interval. One of
|
boot.B |
A single positive integer greater or equal to 10 for the number
of bootstrap replicates for the computation of the bootstrap confidence
interval(s), to be used when |
boot.method |
Method used for bootstrapping. One of
|
... |
additional arguments. |
Value
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in percentage (by default 2.5 percent and 97.5 percent).
Author(s)
Jorge Cabral, jorgecabral@ua.pt
Examples
res_gce_package <-
lmgce(y ~ .,
data = dataGCE,
boot.B = 50,
seed = 230676)
confint(res_gce_package, method = "percentile")
confint(res_gce_package, which = "NormEnt", level = 0.99)
confint(res_gce_package, parm = c("X005"), level = 0.99)