confint-methods {distrMod} | R Documentation |
Methods for function confint
in package distrMod;
by default uses confint
and its corresponding
S3-methods, but also computes
(asymptotic) confidence intervals for objects of class Estimate
.
Computes confidence intervals for one or more parameters in a fitted
model.
confint(object, method, ...) ## S4 method for signature 'ANY, missing': confint(object, method, parm, level = 0.95, ...) ## S4 method for signature 'Estimate, missing': confint(object, method, level = 0.95) ## S4 method for signature 'mle, missing': confint(object, method, parm, level = 0.95, ...) ## S4 method for signature 'profile.mle, missing': confint(object, method, parm, level = 0.95, ...)
object |
in default / signature ANY case: a fitted model object,
in signature Estimate case, an object of class Estimate |
parm |
only used in default / signature ANY case:
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. |
method |
not yet used (only as missing ; later to allow
for various methods |
... |
additional argument(s) for methods. |
confint
is a generic function. Its behavior differs according to
its arguments.
ANY,missing
:confint
.Estimate,missing
:asvar
in argument object
. Besides the actual bounds, organized in
an array just as in the S3 generic, the return value also captures
the name of the estimator for which it is produced, as well as the corresponding
call producing the estimator, and the corresponding
trafo
and nuisance
slots/parts.signature |
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 % (by default 2.5% and 97.5%). |
signature |
An object of class Confint |
confint
,
confint.glm
and confint.nls
in
package MASS, Confint-class
.
## for signature ANY examples confer stats::confint ## (empirical) Data x <- rgamma(50, scale = 0.5, shape = 3) ## parametric family of probability measures G <- GammaFamily(scale = 1, shape = 2) ## Maximum likelihood estimator res <- MLEstimator(x = x, ParamFamily = G) confint(res) ### for comparison: require(MASS) (res1 <- fitdistr(x, "gamma")) ## add a convenient (albeit wrong) ## S3-method for vcov: ## --- wrong as in general cov-matrix ## will not be diagonal ## but for conf-interval this does ## not matter... vcov.fitdistr <- function(object, ...){ v<-diag(object$sd^2) rownames(v) <- colnames(v) <- names(object$estimate) v} ## explicitely transforming to ## MASS parametrization: mtrafo <- function(x){ nms0 <- names(c(main(param(G)),nuisance(param(G)))) 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)} G2 <- G trafo(G2) <- mtrafo res2 <- MLEstimator(x = x, ParamFamily = G2) old<-getdistrModOption("show.details") distrModoptions("show.details" = "minimal") res res1 res2 confint(res) confint(res1) confint(res2) confint(res,level=0.99) distrModoptions("show.details" = old)