confint-methods {distrMod}

Methods for function confint in Package ‘distrMod’

Description

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.

Usage

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, ...)

Arguments

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.

Details

confint is a generic function. Its behavior differs according to its arguments.

signature ANY,missing:

the default method; uses the S3 generic of package stats, see confint; its return value is 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 Estimate,missing:

will return an object of class Confint which corresponds to a confidence interval assuming asymptotic normality, and hence needs suitably filled slot 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.

See Also

confint, confint.glm and confint.nls in package MASS, Confint-class.

Examples

## 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)