qualityTools (version 1.55)

mvPlot: Multi-Vari-Charts

Description

Draws a Multi-Vari Chart for 2, 3 or 4 factors.

Usage

mvPlot(response, fac1, fac2, fac3 = NA, fac4 = NA, sort = TRUE, col, pch, 
       cex.txt = 1, las = 1, labels = FALSE, quantile = TRUE, FUN = NA)

Arguments

response

the values of the response in a vector.response must be declared.

fac1

vector providing factor 1 as shown in the example.fac1 must be declared.

fac2

vector providing factor 2 as shown in the example.fac2 must be declared.

fac3

(optional) vector providing factor 3 as shown in the example. By default fac3 is set to NA.

fac4

(optional) vector providing factor 4 as shown in the example. By default fac3 is set to NA.

sort

logical value indicating whether the sequence of the factors given by fac1 - fac4 should be reordered to minimize the space needed to visualize the Multi-Vari-Chart. By default sort is set to TRUE.

col

graphical parameter. Vector containing numerical values or character strings giving the colors for the different factors. By default col starts with the value 3 and is continued as needed.

pch

graphical parameter. Vector containing numerical values or single characters giving plotting points for the different factors. See points for possible values and their interpretation. Note that only integers

cex.txt

a numerical value giving the amount by which plotting labels at the single points should be magnified relative to the default. By default cex.txt is set to 1.

las

graphical parameter for the style of x-axis labels. See par for further information.

labels

logical value indicating whether the single points should be labeld with the row-number of the data.frame invisibly returned by the function mvPlot. By default labels is set to FALSE.

quantile

logical value indicating whether the quanitiles (0.00135, 0.5 & 0.99865) should be visualized for the single groups. By default quantile is set to TRUE.

FUN

function to be used for calculation of response for unique settings of the factors e.g. the mean. By default FUN is set to NA and therfore omitted.

Value

• mvPlot returns invisibly a data.framein which all plotted points are listed. The option labels can be used to plot the row-numbers at the single points and to ease the identification.

See Also

http://www.r-qualitytools.org

Examples

#Example I
examp1 = expand.grid(c("Engine1","Engine2","Engine3"),c(10,20,30,40))                  
examp1 = as.data.frame(rbind(examp1, examp1, examp1))
examp1 = cbind(examp1, rnorm(36, 1, 0.02))
names(examp1) = c("factor1", "factor2", "response")
test1=mvPlot(response = examp1[,3], fac1 = examp1[,2],
             fac2 = examp1[,1],sort=FALSE,las=2,FUN=mean) 

#Example II
examp2=expand.grid(c("Op I","Op II","Op III"),c(1,2,3,4),
                   c("20.11.1987","21.11.1987"))
examp2=as.data.frame(rbind(examp2, examp2, examp2))
examp2=cbind(examp2, rnorm(72, 22, 2))
names(examp2) = c("factor1", "factor2", "factor3", "response")
test2=mvPlot(response = examp2[,4], fac1 = examp2[,1],
            fac2 = examp2[,2], fac3 = examp2[,3], sort=TRUE, FUN=mean, 
            labels=TRUE)

#Example III
examp3 = expand.grid(c("A","B","C"),c("I","II","III","IV"),c("H","I"),
                     c(1,2,3,4,5))
examp3 = as.data.frame(rbind(examp3, examp3, examp3))
examp3 = cbind(examp3, rnorm(360, 0, 2))
names(examp3) = c("factor1", "factor2", "factor3", "factor4", "response")
test3=mvPlot(response = examp3[,5], fac1 = examp3[,1],
             fac2 = examp3[,2], fac3 = examp3[,3], fac4 = examp3[,4], sort=TRUE, 
             quantile=TRUE, FUN=mean)