uncertaintyBudget.default: Generic function for calling an uncertainty budget object

In uncertainty: Uncertainty Estimation and Contribution Analysis

Description

Creates an uncertainty budget.

Usage

## Default S3 method:
uncertaintyBudget(x, y, ...)

Arguments

x	a list with the vector entries name, label, mean, u(uncertainty), distribution and dof, one for each input quantity.
y	a correlation matrix of the input quantities, interpreted in the same order of input quantities as the vector name
...	additional parameters

Details

Creates an uncertainty budget object

Value

An uncertainty budget object with attributes:

name the name of each input quantity

mean the mean value of each input quantity

u the uncertainty of each input quantity

dofthe degrees of freedom of each input quantity

labelthe label of each input quantity

distribution the distribution of each input quantity, valid values are (bernoulli, beta, binomial, cuachy, chisq, exp, f, gamma, lognormal, poission, normal, unif, t, traingular, weibull, arcsine)

cor the correlation matrix among the input quantities

Note

none

Author(s)

H. Gasca-Aragon

Maintainer: H. Gasca-Aragon <[e-mail]>

References

JCGM 100:2008. Guide to the expression of uncertainty of measurement

JCGM 100:2005. Supplement 1 Propagation of distributions usign a Monte Carlo method

EURACHEM/CITAC Guide CG 4. Quantifying Uncertainty in Analytical Measurement

Becker, R.A., Chambers, J.M. and Wilks, A.R. (1988) The New S Language. Wadsworth & Brooks/Cole.

See Also

uncertaintyBudget, uncertainty, print.uncertaintyBudget

Examples

require(mvtnorm)

cor.mat<- matrix(c(1,-0.7,-0.7,1),2,2)

u.budget<- uncertaintyBudget(x=list(name=c("x0","x1"), 
	mean=c(10,20), u=c(1,5), dof=c(10,10),
	label=c("x[0]", "x[1]"), distribution=c("normal","normal")), y=cor.mat)
u.budget

uncertainty documentation built on May 2, 2019, 7:03 a.m.