Learn R Programming

qualityTools (version 1.55)

errorPlot: Function to create error Charts

Description

The data from an object of class gageRR can be analyzed by running “Error Charts” of the individual deviations from the accepted rference values. These “Error Charts” are provided by the function errorPlot.

Usage

errorPlot(x, main, xlab, ylab, col, pch, type, ylim, legend=TRUE, ...)

Arguments

x
needs to be an object of class gageRR.
main
a main title for the plot.
xlab
a label for the x axis.
ylab
a label for the y axis.
col
plotting color.
pch
an integer specifying a symbol or a single character to be used as the default in plotting points.
type
graphical parameter (see plot).
ylim
the y limits of the plot
legend
a logical value specifying whether a legend is plotted automatically. By default legend is set to ‘TRUE’. If the argument legend is set to ‘FALSE’ an individual legend can be added by using the function legend afterwards.
...
arguments to be passed to methods, such as graphical parameters (see par).

Details

The plotted values are can be calculated in two ways:
  • Error = Observed Value - Reference Value (not yet implemented)
  • Error = Observed Value - Average Measurement of Part

The first way is not yet implemented, because it is not yet possible to give a refrence value to the object in x. This will be implemented later! Therefore errorPlot uses the second way above to calculate the plotted error. Graphical parameters such as col or pch can be given as single characters or as vectors containing characters or number for the parameters of the individual operators.

References

The idea of the plot and the example given by example(errorPlot) are out of:
  • CHRYSLER Group LLC; FORD Motor Company; GENERAL MOTORS Corporation: Measurement System Analysis (MSA), p.112, 4rd ed. Southfield: AIAG, 2010.

See Also

gageRR par http://www.r-qualitytools.org

Examples

Run this code
#create gageRR-object
gdo = gageRRDesign(Operators = 3, Parts = 10, Measurements = 3,  
                   randomize = FALSE)
#vector of responses                   
y = c(0.29,0.08, 0.04,-0.56,-0.47,-1.38,1.34,1.19,0.88,0.47,0.01,0.14,-0.80,       
      -0.56,-1.46, 0.02,-0.20,-0.29,0.59,0.47,0.02,-0.31,-0.63,-0.46,2.26,
      1.80,1.77,-1.36,-1.68,-1.49,0.41,0.25,-0.11,-0.68,-1.22,-1.13,1.17,0.94,
      1.09,0.50,1.03,0.20,-0.92,-1.20,-1.07,-0.11, 0.22,-0.67,0.75,0.55,0.01,
      -0.20, 0.08,-0.56,1.99,2.12,1.45,-1.25,-1.62,-1.77,0.64,0.07,-0.15,-0.58,
      -0.68,-0.96,1.27,1.34,0.67,0.64,0.20,0.11,-0.84,-1.28,-1.45,-0.21,0.06,
      -0.49,0.66,0.83,0.21,-0.17,-0.34,-0.49,2.01,2.19,1.87,-1.31,-1.50,-2.16)
#appropriate responses      
response(gdo)=y                                                                
# perform and gageRR    
gdo=gageRR(gdo)                                                                    
errorPlot(gdo)                                                            

Run the code above in your browser using DataLab