mvPlot: Multi-Vari-Charts
In qualityTools: Statistical Methods for Quality Science

Description Usage Arguments Value Author(s) See Also Examples

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

1 2	mvPlot(response, fac1, fac2, fac3 = NA, fac4 = NA, sort = TRUE, col, pch, cex.txt = 1, las = 1, labels = FALSE, quantile = TRUE, FUN = NA)

`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 and single-character strings can be set as a graphics parameter (and not NA nor NULL). By default `pch` starts with the value ‘1’ and is continued as needed.
`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.

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.

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

http://www.r-qualitytools.org

#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)