Confint-class
Return value S4 classes for method “confint”.
Objects could in principle be created by calls of the
form new("Confint", ...).
The preferred form is to have them created via a call to
confint.
typeObject of class "character":
type of the confidence interval (asymptotic, bootstrap,...).
Can be of length >2. Then in printing, the first element
is printed in the gap '[...]' in 'an [...] confidence interval',
while the other elements are printed below.
confintObject of class "array":
the confidence interval(s).
call.estimateObject of class "call":
the estimate(s) for which the confidence intervals are produced.
name.estimateObject of class "character":
the name of the estimate(s) for which the confidence intervals are produced.
samplesize.estimate:Object of class "numeric":
the sample size of the estimate(s) for which the confidence intervals
are (only complete cases) produced.
completecases.estimate:Object of class "logical":
complete cases at which the estimate was evaluated.
trafo.estimateObject of class "matrix":
the trafo/derivative matrix of the estimate(s) for which
the confidence intervals are produced.
nuisance.estimateObject of class "OptionalNumeric":
the nuisance parameter (if any) at which the confidence
intervals are produced.
fixed.estimateObject of class "OptionalNumeric":
the fixed part of the parameter (if any) at which the confidence
intervals are produced.
signature(object = "Confint"):
accessor function for slot type.
signature(object = "Confint", method = "missing"):
accessor function for slot type.
signature(object = "Confint"):
accessor function for slot call.estimate.
signature(object = "Confint"):
accessor function for slot name.estimate.
signature(object = "Confint"):
accessor function for slot trafo.estimate.
signature(object = "Confint"):
(with additional argument onlycompletecases
defaulting to TRUE returns the sample size;
in case there are any incomplete cases and argument
onlycompletecases is FALSE, the number of
these is added to slot samplesize.
signature(object = "Confint"):
accessor function for slot completecases.estimate.
signature(object = "Confint"):
accessor function for slot nuisance.estimate.
signature(object = "Confint"):
accessor function for slot fixed.estimate.
signature(object = "Confint"): shows a detailed view
of the object; slots nuisance.estimate and
fixed.estimate are only shown if non-null,
and slot trafo.estimate only if different from a unit matrix.
signature(object = "Confint"): just as show,
but with additional arguments digits.
Detailedness of output by methods show, print is controlled
by the global option show.details to be set by
distrModoptions.
As method show is used when inspecting an object by typing the object's
name into the console, show comes without extra arguments and hence
detailedness must be controlled by global options.
Method print may be called with a (partially matched) argument
show.details, and then the global option is temporarily set to this
value.
More specifically, when show.detail is matched to "minimal"
you will be shown only the type of the confidence interval(s) and its/their
values. When show.detail is matched to "medium", you will in
addition see the type of the estimator(s) for which it is produced,
the corresponding call of the estimater, its sample size, and, if present, the
value of the corresponding nuisance parameter.
Finally, when show.detail is matched to "maximal", additionally
you will be shown the fixed part of the parameter (if present) and
the transformation of the estimator (if non-trivial, i.e. the
identity) in form of its function code respectively of its derivative matrix.
The pretty-printing code for methods show and print
has been borrowed from confint.default in package stats.
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
## some transformation
mtrafo <- function(x){
nms0 <- c("scale","shape")
nms <- c("shape","rate")
fval0 <- c(x[2], 1/x[1])
names(fval0) <- nms
mat0 <- matrix( c(0, -1/x[1]^2, 1, 0), nrow = 2, ncol = 2,
dimnames = list(nms,nms0))
list(fval = fval0, mat = mat0)}
x <- rgamma(50, scale = 0.5, shape = 3)
## parametric family of probability measures
G <- GammaFamily(scale = 1, shape = 2, trafo = mtrafo)
## MLE
res <- MLEstimator(x = x, ParamFamily = G)
ci <- confint(res)
print(ci, digits = 4, show.details="maximal")
print(ci, digits = 4, show.details="medium")
print(ci, digits = 4, show.details="minimal")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.