uncertainty.default: Generic function for calling an uncertainty object

In uncertainty: Uncertainty Estimation and Contribution Analysis

Generic function for calling an uncertainty object

Description

Creates an uncertainty estimation object using a measurand model and an uncertainty budget object

Usage

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

Arguments

x	an uncertainty budget object
y	a list with the measurand description and selected estimation method, the measurand includes: measurand_name, measurand_model, measurand_label, measurand_description, alpha (significance level), method and method parameters. the valid methods are: GFO, GSO, MC. currently the only method parameter implemented is the number of simulated samples (B) for the method MC. use.correlation is a boolean field, if there are correlations and this flag is TRUE then the correlation is used to adjust the effective degrees of freedom for correlation, according to Castrup adjustment to Welch-Satterthwaite algoritm. if missing or NULL it is assumed as FALSE
...	additional parameters

Details

Creates an uncertainty estimation object. Uses an uncertainty budget object to estimate the expected value and uncertainty of a measurand by applying a selected estimation method.

Value

An uncertainty estimation object with the structure: method selected estimating method, call current call invocation, uncertaintyBudget an uncertainty budget object, measurand name, label, model describing the measurand, mean the estimated mean, sd the estimated standard deviation, u the estimated standard uncertainty, alpha the significante level used in the estimation, dof the estimated degrees of freedom, U the estimated expanded uncertainty, lcl the lower confidence interval, ucl the upper confidence interval, variables a vector with the input quantities, contribution a vector with the uncertainty contributions, cor.contribution the uncertainty contribution due to overall correlation, partial a vector of the partial derivatives of the measurand.model with respect to each input quantity, coeff a vector of the sensibility coefficients for each input quantity.

Note

none

Author(s)

Hugo Gasca-Aragon

Maintainer: Hugo Gasca-Aragon <[e-mail]>

References

JCGM 200:2012. International vocabulary of metrology—Basic and general concepts and associated terms (VIM)

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

See Also

uncertainty, uncertaintyBudget.default, print.uncertainty, plot.uncertainty, summary.uncertainty

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), units = c("kg", "kg"), u = c(1, 5), dof = c(10, 10),
	label = c("x[0]", "x[1]"), distribution = c("normal", "normal"),
	description = c("measurand mass", "sample mass"),
	type = c("A", "A")), 
	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",
	 measurand_description = "ratio of masses",
         method = "GFO", alpha = 0.05))

GFO.res

uncertainty documentation built on Dec. 15, 2025, 1:06 a.m.