RSA (version 0.5.1)

plotRSA: Plots a response surface of a polynomial equation of second degree

Description

Plots an RSA object, or a response surface with specified parameters

Usage

plotRSA(x = NULL, y = 0, x2 = 0, y2 = 0, xy = 0, w = 0,
    wx = 0, wy = 0, b0 = 0, xlim = NULL, ylim = NULL,
    zlim = NULL, xlab = NULL, ylab = NULL, zlab = NULL,
    surface = "predict", lambda = NULL,
    rot = list(x = -45, y = 45, z = 35),
    label.rot = list(x = 45, y = -25, z = 94),
    gridsize = 21, bw = FALSE, legend = TRUE,
    showSP = TRUE, axes = c("LOC", "LOIC", "PA1", "PA2"),
    cex = 1.2, type = "3d", points = FALSE, model = "full",
    demo = FALSE, fit = NULL, link = "identity",
    distance = c(1, 1, 1), tck = c(1, 1, 1),
    showBorder = TRUE, showContour = FALSE, pal = NULL,
    ...)

Arguments

x

Either an RSA object (returned by the RSA function), or the coefficient for the X predictor

y

Y coefficient

x2

X^2 coefficient

y2

Y^2 coefficient

xy

XY interaction coefficient

w

W coefficient (for (un)constrained absolute difference model)

wx

WX coefficient (for (un)constrained absolute difference model)

wy

WY coefficient (for (un)constrained absolute difference model)

b0

Intercept

xlim

Limits of the x axis

ylim

Limits of the y axis

zlim

Limits of the z axis

xlab

Label for x axis

ylab

Label for y axis

zlab

Label for z axis

surface

Method for the calculation of the surface z values. "predict" takes the predicted values from the model, "smooth" uses a thin plate smoother (function Tps from the fields package) of the raw data

lambda

lambda parameter for the smoother. Default (NULL) means that it is estimated by the smoother function. Small lambdas around 1 lead to rugged surfaces, big lambdas to very smooth surfaces.

rot

Rotation of the 3d surface plot (when type == "3d")

label.rot

Rotation of the axis labls (when type == "3d")

gridsize

Number of grid nodes in each dimension

bw

Print surface in black and white instead of colors?

legend

Print color legend for z values?

cex

Font size factor for axes labels

type

3d for 3d surface plot, contour for 2d contour plot, "interactive" for interactive rotatable plot. Shortcuts (i.e., first letter of string) are sufficient

points

Should the original data points be overplotted?

model

If x is an RSA object: from which model should the response surface be computed?

demo

Do not change that parameter (internal use only)

fit

Do not change that parameter (internal use only)

showSP

Should the surface parameters a1 to a4 be shown on the plot? In case of a 3d plot a1 to a4 are printed on the upper left side; in case of a contour plot the principal axes are plotted.

axes

A vector of strings specifying the axes that should be plotted. Can be any combination of c("LOC", "LOIC", "PA1", "PA2"). LOC = line of congruence, LOIC = line of incongruence, PA1 = first principal axis, PA2 = second principal axis

link

Link function to transform the z axes. Implemented are "identity" (no transformation; default), "probit", and "logit"

showBorder

Should a thicker border around the surface be plotted? Sometimes this border leaves the surrounding box, which does not look good. In this case the border can be suppressed by setting showBorder=FALSE.

showContour

Should the contour lines be plotted on the 3d wireframe plot? (Parameter only relevant for type="3d")

distance

A vector of three values defining the distance of labels to the axes

tck

A vector of three values defining the position of labels to the axes (see ?wireframe)

pal

A palette for shading

...

Additional parameters apssed to the plotting function (e.g., main="Title"). A useful title might be the R squared of the plotted model: main = as.expression(bquote(R^2==.(round(getPar(x, "r2", model="full"), 3))))

Details

Each plot type has its distinctive advantages. The two-dimensional contour plot gives a clear view of the position of the principal axes and the stationary point. The 3d plot gives a three dimensional impression of the surface, allows overplotting of the original data points (in case an RSA object is provided), and allows the interactive adjustment of regression weights in the demoRSA function. The interactive plot allows rotating and exploring a three-dimensional surface with the mouse (nice for demonstration purposes). If you want to export publication-ready plots, it is recommended to export it with following commands: p1 <- plot(r1, bw=TRUE) trellis.device(device="cairo_pdf", filename="RSA_plot.pdf") print(p1) dev.off()

See Also

demoRSA, RSA

Examples

# Plot response surfaces from known parameters
# example of Edwards (2002), Figure 3
plotRSA(x=.314, y=-.118, x2=-.145, y2=-.102, xy=.299, b0=5.628)
plotRSA(x=.314, y=-.118, x2=-.145, y2=-.102, xy=.299, b0=5.628, type="c")

# Plot response surface from an RSA object
set.seed(0xBEEF)
n <- 300
err <- 2
x <- rnorm(n, 0, 5)
y <- rnorm(n, 0, 5)
df <- data.frame(x, y)
df <- within(df, {
	diff <- x-y
	absdiff <- abs(x-y)
	sqdiff <- (x-y)^2
	z.diff <- diff + rnorm(n, 0, err)
	z.abs <- absdiff + rnorm(n, 0, err)
	z.sq <- sqdiff + rnorm(n, 0, err)
	z.add <- diff + 0.4*x + rnorm(n, 0, err)
	z.complex <- 0.4*x + - 0.2*x*y + + 0.1*x^2 - 0.03*y^2 + rnorm(n, 0, err)
})

r1 <- RSA(z.sq~x*y, df)
plot(r1)
plot(r1, points=TRUE, model="sqdiff")