averagePlot: Function to create average Plots

In qualityTools: Statistical Methods for Quality Science

Description

averagePlot creates all x-y plots of averages by size out of an object of class gageRR.
Therfore the averages of the multiple readings by each operator on each part are plotted with the reference
value or overall part averages as the index.

Usage

 averagePlot(x, main, xlab, ylab, col, ask=TRUE, single=FALSE, ...)

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
ask	a logical value. If ‘TRUE’ (default) the user is asked for input, before a new figure is drawn.
single	a logical value.If ‘TRUE’ a new graphic device will be opened for each plot. By default single is set to ‘FALSE’. For further information see details.
...	arguments to be passed to methods, such as graphical parameters (see par).

Details

averagePlot will split the screen into maximal 3x2 subscreens in which plots will be plotted.
If the six subscreens are not enough the function will (by default) ask the user before plotting
the next few plots. If ask is set to ‘FALSE’ the function will open as many graphic
devices as necessary to show all plots.
There are two possible ways to avoid the described internal routine of splitting the screen:

• If single is set to ‘TRUE’ all plots will be plotted in seperate single devices.
  

• If par(mfrow) is unequal to ‘c(1,1)’ the function will adapt the setting given by par.

Note

Please do read the vignette for the package qualityTools at http://www.r-qualitytools.org.

Author(s)

Thomas Roth: [e-mail]
Etienne Stockhausen: [e-mail]

References

The idea of the plot and the example given by example(averagePlot) are out of:

• CHRYSLER Group LLC; FORD Motor Company; GENERAL MOTORS Corporation: Measurement System Analysis (MSA),
  p.114, 4rd ed. Southfield: AIAG, 2010.
  

See Also

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

Examples

# 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)                                                                    
averagePlot(gdo,pch=19)                                                            

Example output

Loading required package: Rsolnp
Loading required package: MASS

Attaching package: 'qualityTools'

The following object is masked from 'package:stats':

    sigma


AnOVa Table -  crossed Design
              Df Sum Sq Mean Sq F value   Pr(>F)    
Operator       2   3.17   1.584  34.440 1.09e-10 ***
Part           9  88.36   9.818 213.517  < 2e-16 ***
Operator:Part 18   0.36   0.020   0.434    0.974    
Residuals     60   2.76   0.046                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------
AnOVa Table Without Interaction -  crossed Design
            Df Sum Sq Mean Sq F value   Pr(>F)    
Operator     2   3.17   1.584   39.62 1.34e-12 ***
Part         9  88.36   9.818  245.61  < 2e-16 ***
Residuals   78   3.12   0.040                     
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

----------

Gage R&R
                 VarComp VarCompContrib Stdev StudyVar StudyVarContrib
totalRR           0.0914         0.0776 0.302     1.81           0.279
 repeatability    0.0400         0.0339 0.200     1.20           0.184
 reproducibility  0.0515         0.0437 0.227     1.36           0.209
   Operator       0.0515         0.0437 0.227     1.36           0.209
   Operator:Part  0.0000         0.0000 0.000     0.00           0.000
Part to Part      1.0864         0.9224 1.042     6.25           0.960
totalVar          1.1779         1.0000 1.085     6.51           1.000

---
 * Contrib equals Contribution in %
 **Number of Distinct Categories (truncated signal-to-noise-ratio) = 4 

NULL

qualityTools documentation built on May 2, 2019, 10:21 a.m.