gumCV: Combination of Variances

In ppernot/rgumlib: Uncertainty Propagation (GUM & GUM-Supp1) and Sensitivity Analysis

Description

Uncertainty propagation by combination of variances (GUM).

Usage

gumCV(fExpr, x.mu, x.u, x.cor = diag(length(x.mu)), x.cov = NULL,
  budgetTable = TRUE, silent = FALSE,
  tol = sqrt(.Machine$double.eps))

Arguments

fExpr	An expression or a function object. For an expression, all variables will be considered as uncertain. For a function the list of uncertain variables is derived from the list of arguments.
x.mu	Named vector of mean values with names compatible with fExpr.
x.u	Named vector of standard uncertainty values (one of {x.u, x.cov} mandatory).
x.cor	Named correlation matrix between model parameters
x.cov	Named variance/covariance matrix between model parameters (one of {x.u, x.cov} mandatory).
budgetTable	Flag to controle cmputation of the budget table.
silent	Flag to execute gumCV without printout.
tol	Numeric tolerance level to check positive-definiteness of x.cor or x.cov.

Value

A list containing:

y.mu	mean value of model
y.u	standard uncertainty of model
anova	(vector) relative contributions of parameters to y variance
anovaCov	global relative contribution of parameters covariance to Y variance
budget	(dataframe) uncertainty budget table, mostly to be printed

References

(GUM) Evaluation of measurement data - Guide to the expression of uncertainty in measurement. JCGM 100:2008. http://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf

ppernot/rgumlib documentation built on May 25, 2019, 11:24 a.m.