Function to visualize and calucalte the linearity of a gage.

Description

Function visualize the linearity of a gage by plotting the single and mean bias in one plot and intercalate them with a straight line.
Furthermore the function deliver some characteristic values of linearity studies according to MSA (Measurement System Analysis).

Usage

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gageLin(object, conf.level = 0.95, ylim, col, pch, lty = c(1, 2), 
        stats = TRUE, plot = TRUE)

Arguments

object

an object of class MSALinearity. To create such an object see gageLinDesign.

conf.level

an numeric value between ‘0’ and ‘1’, giving the confidence intervall for the analysis.
Default value: ‘0.95’

ylim

a vector with two entries, giving the minimum and the maximum of the y-axis.

col

a vector with four numeric entries. The first gives the color of the single points, the second gives the color of the points for the mean bias, the third gives the color fo the straight interpolation line and the fourth gives the color for the lines representing the confidence interval. If one of the values is missing or negative the points or lines are not plotted. col is by default ‘c(1,2,1,4)’

pch

a vector with two numeric or single character entries giving the symbols for the single points (1st entry) and the mean bias (2nd entry). The default vector is “c(20,18)”

lty

a vector with two entries giving the line-style for the interpolating line and the confidence interval lines. For detailed information to the entries please see par. The default value for lty is ‘c(1,2)’.

stats

a logigal value. If ‘TRUE’ (default) the function returns all calculated information.

plot

a logigal value. If ‘TRUE’ (default) the function deliver a plot.

Value

The function returns an object of class MSALinearity which can be used with e.g. plot or summary.

Author(s)

Thomas Roth: thomas.roth@tu-berlin.de
Etienne Stockhausen: stocdarf@mailbox.tu-berlin.de

References

  • Cgrysler Group LCC & Ford Motor Company & General Motors Corporation, Measurement System Analysis - MSA (2010), 4th ed. Southfield,Michigan: Automotive Industry Action Group.

See Also

cg
gageRR
gageLinDesign
response
edit
http://www.r-qualitytools.org

Examples

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# Results of single runs
A=c(2.7,2.5,2.4,2.5,2.7,2.3,2.5,2.5,2.4,2.4,2.6,2.4)  
B=c(5.1,3.9,4.2,5,3.8,3.9,3.9,3.9,3.9,4,4.1,3.8)
C=c(5.8,5.7,5.9,5.9,6,6.1,6,6.1,6.4,6.3,6,6.1)
D=c(7.6,7.7,7.8,7.7,7.8,7.8,7.8,7.7,7.8,7.5,7.6,7.7)
E=c(9.1,9.3,9.5,9.3,9.4,9.5,9.5,9.5,9.6,9.2,9.3,9.4)

# creates Desing
test=gageLinDesign(ref=c(2,4,6,8,10),n=12)
 # creates data.frame with results             
Messungen=data.frame(rbind(A,B,C,D,E))
# enter results in Desing               
response(test)=Messungen                              

# no plot and no return
MSALin=gageLin(test,stats=FALSE,plot=FALSE)
# plot only           
plot(MSALin)
# summary                                          
summary(MSALin)                                       

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