summary.imprecise: Summarizing Imprecise Class Objcects
In ipeglim: Imprecise Inferential Framework on Statistical Reasoning

Description Usage Arguments Details Value Author(s) References

The function summary.imprecise is the imprecise method of generic function summary which is used for producing summaries of the results from various model fitting functions performed on the imprecise inferential framework. See ‘Details’.

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  ## S3 method for class 'imprecise'
 summary(object, HT.est = FALSE,
    silent = FALSE, ...)

`object`	the object of class `imprecise`.
`HT.est`	a logical value; Defaults to `FALSE`. Would like to see Horvitz-Thompson estimator?
`silent`	a logical value; Would like to see the report of progress messages (including warnings and error messages) generated from numerical methods that are used for a numerical approximation? Defaults to `FALSE`.

Object summaries depend on the option chosen in the method. The commonly returned object is est which is a collection of all Bayes estimates from the imprecise posterior.

The Horvitz-Thompson estimator is the implementation of that in the study of Heijden 2003. HT.est=TRUE is not allowed when ztrunc=TRUE.

A list with the following compoentns:

`est`	a list of vectors or matrices of the estimates of canonical parameters.
`N`	Horvitz-Thompson estimates if `HT.est=TRUE`
`mui`	Estimate of the mean parameter if `xi` is supplied.
`inf`	a numeric vector of length `p`, having an infimum of each canonical parameter.
`sup`	a numeric vector of length `p`, having a supremum of each canonical parameter.
`inf.idx`	an index vector corresponding to `inf` in `est`.
`sup.idx`	an index vector corresponding to `sup` in `est`.
`delta`	the vector of imprecision

Chel Hee Lee <gnustats@gmail.com>

Peter GM van der Heijden, Rami Bustami, Maarten JLF Cruyff, Godfried Engbersen and Hans C van Houwelingen (2003), Point and interval estimation of the population size using the truncated Poisson regression model, Statistical Modelling, 3, pp. 305-322.

Lee (2013) “Imprecise inferential framework”, PhD thesis.

Walley P (1991). _Statistical reasoning with imprecise probabilities_, series Monographs on statistics and applied probability. Chapman and Hall. ISBN 9780412286605, <URL: http://books.google.ca/books?id=Nk9Qons1kHsC>.

ipeglim documentation built on May 2, 2019, 4:31 p.m.