# print.uncertainty: Displays the detailed content of a measurand model including... In uncertainty: Uncertainty Estimation and Contribution Analysis

## Description

Displays the estimated value of the measurand, its standard deviation, its standard uncertainty, the degrees of freedom and the significance level and an CI with that significance level.

## Usage

 ```1 2``` ```## S3 method for class 'uncertainty' print(x, ...) ```

## Arguments

 `x` an uncertainty object `...` additional parameters

none

## Value

None (invisible NULL)

none

## Author(s)

H. Gasca-Aragon

Maintainer: H. Gasca-Aragon <[email protected]>

## 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.

`uncertainty.default`, `print`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```# 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)) # implicit call to print method GFO.res # same as print(GFO.res) # structure of an uncertainty estimation object attributes(GFO.res) ```