plot.uncertainty: Plots a probability density function related to the measurand...

In uncertainty: Uncertainty Estimation and Contribution Analysis

Description

Plot a probability density function attributed to the measurand, depending on the selected method to estimate the uncertainty.

Usage

## S3 method for class 'uncertainty'
plot(x, y = NULL, xlab = parse(text = x$measurand_label), 
main = "", ylab = "Probability density", from = x$mean - 4 * x$u, to = x$mean + 4 * x$u, 
lwd = 2, add = FALSE, ...)

Arguments

x	An uncertainty object
y	not used, exists only for compatibility with the S3 generic function.
xlab	string or expression, label for the x-axis.
main	string or expression, label for the plot.
ylab	string or expression, label for the y-axis.
from	numeric, lower value of the x-axis to display.
to	numeric, upper valur of the x-axis to display.
lwd	numeric, line width.
add	logic, decides to add the curve into an existing plot or to create a new plot.
...	additional parameters.

Details

none

Value

None (invisible NULL)

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

See Also

uncertainty.default, plot

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)

# 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))

# plot the estimated pdf of the measurand
## Not run: plot(GFO.res)

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