qualityTools (version 1.53)

contourPlot: Contour Plot

Description

Creates a contour diagramm for an object of class facDesign.

Usage

contourPlot(x, y, z, data = NULL, xlim, ylim, main, xlab, ylab, form = "fit", 
            col = 1, steps, factors, fun)

Arguments

x

name providing the Factor A for the plot.

y

name providing the Factor B for the plot.

z

name giving the Response variable.

data

needs to be an object of class facDesign and contains the names of x,y,z.

xlim

vector giving the range of the x-axis.

ylim

vector giving the range of the y-axis.

main

an overall title for the plot: see title.

xlab

a title for the x axis: title.

ylab

a title for the y axis: title.

form

a character string or a formula with the syntax y~ x+y + x*y. If form is a character it has to be one out of the following:

• quadratic
• full
• interaction

col

a predefined (1, 2, 3 or 4) or self defined colorRampPalette or color to be used (i.e. red).

steps

number of grid points per factor. By default steps = 25.

factors

list of 4th 5th factor with value i.e. factors = list(D = 1.2, E = -1), if nothing is specified values will be the mean of the low and the high value of the factors.

fun

function to be applied to z desirability.

Value

• The function contourPlot() returns an invisible list with the following entries:
  • x - locations of grid lines for x at which the values in z are measured
  • y - locations of grid lines for y at which the values in z are measured
  • z - a matrix containing the values of z to be plotted

Details

This function can be used to display the desirability of each response by specifying fun = desirability or the fun = overall (i.e. composed) desirability of all responses. The required desirabilities can be set using desires.

See Also

wirePlot filled.contour persp link{colorRampPalette} http://www.r-qualitytools.org/Improve.html

Examples

#create a response surface design and assign random data to response y
fdo = rsmDesign(k = 3, blocks = 2)
response(fdo) = data.frame(y = rnorm(nrow(fdo)))
par(mfrow = c(2,3))

#I - display linear fit
contourPlot(A,B,y, data = fdo, form = "linear")
#II - display full fit (i.e. effect, interactions and quadratic effects
contourPlot(A,B,y, data = fdo, form = "full")
#III - display a fit specified before
fits(fdo) = lm(y ~ B + I(A^2) , data = fdo)
contourPlot(A,B,y, data = fdo, form = "fit")
#IV - display a fit given directly
contourPlot(A,B,y, data = fdo, form = "y ~ A*B + I(A^2)")
#V - display a fit using a different colorRamp
contourPlot(A,B,y, data = fdo, form = "full", col = 2)
#VI - display a fit using a self defined colorRamp
myColour = colorRampPalette(c("green", "gray","blue"))
contourPlot(A,B,y, data = fdo, form = "full", col = myColour)