summary.uncertainty {uncertainty}

Creates an uncertainty summary object

Description

Performs an uncertainty contribution estimation for the uncertainty object. The metric used to measure the contribution is percent of variance. If correlation is present an additional entry is shown with the whole contribution due to correlated input quantities.

Usage

## S3 method for class 'uncertainty'
summary(object, ndigits = 3, ...)

Arguments

object

an uncerainty object

ndigits

numeric, the number of digits for displaying.

...

additional parameters

Details

none

Value

An uncertainty summary object:

call

the call invocation

measurand.name

name of the measurand

measurand.label

label of the measurand for displaying purposes

budget

a list with the name, mean, label, u(uncertainty), dof and uncertainty contribution for each input quantity plus a correlation entry if any

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

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

uncertainty.default, print.summary.uncertainty, summary

Examples

# create an uncertainty budget
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

# estimate the measurand uncertainty using an uncertainty budget,
# a measurand definition and a selected estimating method.
GFO.res<- uncertainty(x=u.budget, 
y=list(measurand_name="ratio.GFO", measurand_label="ratio[GFO]", 
measurand_model="x0/x1", method="GFO", alpha=0.05))

GFO.res

# create an uncertainty summary object
GFO.sum<- summary(GFO.res)

# implicit call to the print method
GFO.sum

# same as
print(GFO.sum)

# uncertainty summary structure
attributes(GFO.sum)