Description Usage Arguments Details Value Author(s) References See Also Examples
A Signal-to-Noise-Ratio plot is created for designs of type taguchiDesign with at least two replicates.
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object |
needs to be an object of class |
type |
character variable setting the type of the signal-to-noise-ratio plot. The following three can be chosen:
By default |
factors |
for which factor is the effectPlot to be created. |
fun |
a function for the construction of the effectPlot such as |
response |
response variable. If the response data frame of fdo consists of more then one responses, |
single |
logical value. If ‘TRUE’ device region can be set up using for instance |
points |
logical value. If ‘TRUE’ points are shown in addition to values out of |
classic |
logical value. ‘TRUE’ creates an effectPlot as depicted in most textbooks. |
axes |
logical value indicating wheter the axes should be drawn or not. |
lty |
numerical value which specifies the line type used. |
xlab |
a title for the x axis: |
ylab |
a title for the y axis: |
main |
an overall title for the plot: see |
ylim |
vector giving the range of the y-axis. |
... |
Arguments to be passed to methods, such as graphical parameters (see |
snPlot
uses effectPlot
and creates an effect plot for the signal-to-noise ratios as target values.
Depending on the used type
the target values for the single replications of the taguchi design will be calculated in the following way:
“nominal”: SN = 10*log(mean(y)/var(y))
“smaller”: SN = -10*log((1/n)*sum(y^2))
“larger”: SN = -10*log((1/n)*sum(1/y^2))
Signal-to-Noise ratio plots are an additional tool to estimate the effects of the single factors. Beside the effect plot, which is used to identify the factor with the most effect to a process or something like that, the signal-to-noise ratio plot can be used to judge the variance an d therefore the validity of the results of an effect plot.
snPlot invisibly returns a data.frame containing all the single Signal-to-Noise ratios.
Thomas Roth [email protected]
Etienne Stockhausen [email protected]
APTE, P.R.: Taguchi Method for Dynamic Problems - 3 Day Taguchi Method Workshop at Unimap. Bombay, 2012.
interactionPlot
paretoPlot
facDesign
response
normalPlot
http://www.r-qualitytools.org/html/Improve.html
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