CInp: Construct local confidence intervals from joint empirical...

In BSagri: Safety Assessment in Agricultural Field Trials

Description

Construct local confidence intervals for each parameter from the empirical joint distribution of a parameter vector of length P.

Usage

## Default S3 method:
CInp(x, conf.level = 0.95,
 alternative = "two.sided", ...)

## S3 method for class 'CCRatio'
CInp(x, ...)

## S3 method for class 'CCDiff'
CInp(x, ...)

## S3 method for class 'bugs'
CInp(x, conf.level = 0.95,
 alternative = "two.sided", whichp = NULL, ...)

Arguments

x	an N-times-P matrix, or an object of class CCRatio, CCDiff, bugs, as can be obtained by calling the functions CCRatio, CCDiff, or openbugs in package R2WinBUGS
conf.level	a single numeric value between 0.5 and 1, specifying the local confidence level for each of the P parameters
alternative	a single character string, one of "two.sided", "less", "greater", for two-sided, upper and lower limits
whichp	a single character string, naming an element of the sims.list if x is a bugs object, ignored otherwise
...	currently not used

Details

Construct simple confidence intervals based on order statistics applied to the marginal empirical distributions in x.

Value

An object of class "CInp", a list with elements

conf.int	a P-times-2 matrix containing the lower and upper confidence limits
estimate	a numeric vector of length P, containing the medians of the P marginal empirical distributions
x	the input object
k	the number of values outside each confidence interval, i.e. conf.level*N
N	the number of values used to construct each confidence interval
conf.level	a single numeric value, the nominal confidence level, as input
alternative	a single character string, as input

See Also

The function internally used is quantile with its default settings. See SCSnp for simultaneous sets.

Examples

# Assume a 100 times 4 matrix of 4 mutually independent
# normal variables:

X<-cbind(rnorm(100), rnorm(100), rnorm(100), rnorm(100))

lcits<-CInp(x=X, conf.level=0.95, alternative="two.sided")
lcits

ci1<-lcits$conf.int[1,]
length( which(X[,1]>=ci1[1] & X[,1]<=ci1[2] ) )


ci2<-lcits$conf.int[2,]
length( which(X[,2]>=ci2[1] & X[,2]<=ci2[2] ) )

BSagri documentation built on May 2, 2019, 8:29 a.m.