calibSI: Attempts to find a support interval with the desired...

Description Usage Arguments Value Author(s) Examples

View source: R/calibSI.R

Description

This function performs a grid search to find the lowest support level that has the desired coverage probability. It begins by searching a grid of relative likelihood values using a fixed number of parametric bootstraps at each point. The likelihood value is then refined using a golden section based search.

Usage

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calibSI(dat, n = NULL, family, conf.level = 0.95, B = 2000, 
gridlo = 4, gridhi = 20, gridix = 2, tol = 0.03)

Arguments

dat

This argument is the number of success if family='binomial', the number of occurences if family='poisson', or a vector of normal draws if family='normal'.

n

Number of trials if family='binomial'

family

Data type entered, accepts "binomial", "poisson", "pois", "gaussian", "normal"

conf.level

target confidence level

B

Number of parametric bootstraps to use to estimate coverage probability after the initial grid search.

gridlo

Lowest relative likelihood considered in the initial grid search

gridhi

Highest relative likelihood considered in the initial grid search

gridix

size of steps to be checked between gridlo and gridhi in initial search

tol

acceptable error in the likelihood support level returned

Value

si

The support interval estimated to have the desired confidence level

support.level

The relative likelihood defining the interval's endpoints

init.grid

Relative likelihoods checked as part of the initial gridsearch and their estimated coverage

Author(s)

Derek Smith

Examples

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set.seed(10)
calibSI(rnorm(15), family="normal", conf.level=.95, B=1000)

supportInt documentation built on May 29, 2017, 7:49 p.m.