R2BayesX (version 0.1-1)

plot3d: 3D Effect Plot

Description

Function to plot 3D graphics or image and/or contour plots for bivariate effects/functions, typically used for objects of class "sm.bayesx" and "geo.bayesx" returned from function bayesx and read.bayesx.output.

Usage

plot3d(x, residuals = FALSE, col.surface = NULL, 
  ncol = 99L, swap = FALSE, col.residuals = NULL, col.contour = NULL, 
  c.select = NULL, grid = 30L, image = FALSE, contour = FALSE, 
  legend = TRUE, cex.legend = 1, breaks = NULL, range = NULL, 
  digits = 2L, d.persp = 1L, r.persp = sqrt(3), linear = TRUE, 
  extrap = FALSE, outscale = 0, data = NULL, ...)

Arguments

x

a matrix or data frame, containing the covariates for which the effect should be plotted in the first and second column and at least a third column containing the effect, typically the structure for bivariate functions returned within

residuals

if set to TRUE, partial residuals may also be plotted if available.

col.surface

the color of the surface, may also be a function, e.g. col.surface = heat.colors.

ncol

the number of different colors that should be generated, if col.surface is a function.

swap

if set to TRUE colors will be represented in reverse order.

col.residuals

the color of the partial residuals, or if contour = TRUE the color of the contour lines.

col.contour

the color of the contour lines.

c.select

integer vector of maximum length of columns of x, selects the columns of the resulting data matrix that should be used for plotting. E.g. if x has 5 columns, then c.select = c(1, 2, 5) will sele

grid

the grid size of the surface(s).

image

if set to TRUE, an image.plot is drawn.

contour

if set to TRUE, a contour plot is drawn.

legend

if image = TRUE an additional legend may be added to the plot.

cex.legend

the expansion factor for the legend text, see text.

breaks

a set of breakpoints for the colors: must give one more breakpoint than ncol.

range

specifies a certain range values should be plotted for.

digits

specifies the legend decimal places.

d.persp

see argument d in function persp.

r.persp

see argument r in function persp.

linear

see function interp.

extrap

see function interp.

outscale

scales the outer ranges of x and z limits used for interpolation.

data

if x is a formula, a data.frame or list. By default the variables are taken from environment(x): typically the environment from which plot3d is called.

...

parameters passed to colorlegend if an image plot with legend is drawn, also other graphical parameters, please see the details.

Details

For 3D plots the following graphical parameters may be specified additionally:

• cex: specify the size of partial residuals,
• col: it is possible to specify the color for the surfaces ifse > 0, then e.g.col = c("green", "black", "red"),
• pch: the plotting character of the partial residuals,
• ...: other graphical parameters passed functionspersp,image.plotandcontour.

See Also

plot.bayesx, bayesx, read.bayesx.output, fitted.bayesx colorlegend.

Examples

## generate some data
set.seed(111)
n <- 500

## regressors
dat <- data.frame(z = runif(n, -3, 3), w = runif(n, 0, 6))

## response
dat$y <- with(dat, 1.5 + cos(z) * sin(w) + rnorm(n, sd = 0.6))

## estimate model
b <- bayesx(y ~ sx(z, w, bs = "te", knots = 5), data = dat, method = "REML")
summary(b)

## plot estimated effect
plot(b, term = "sx(z,w)")

## extract fitted effects
f <- fitted(b, term = "sx(z,w)")

## now use plot3d
plot3d(f)
plot3d(f, swap = TRUE)
plot3d(f, residuals = TRUE)
plot3d(f, resid = TRUE, cex.resid = 0.1)
plot3d(f, resid = TRUE, pch = 2, col.resid = "green3")
plot3d(f, resid = TRUE, c.select = 95, cex.resid = 0.1)
plot3d(f, resid = TRUE, c.select = 80, cex.resid = 0.1)
plot3d(f, grid = 100, border = NA)
plot3d(f, c.select = 95, border = c("red", NA, "green"),
  col.surface = c(1, NA, 1), resid = TRUE, cex.resid = 0.2)

## now some image and contour
plot3d(f, image = TRUE, legend = FALSE)
plot3d(f, image = TRUE, legend = TRUE)
plot3d(f, image = TRUE, contour = TRUE)
plot3d(f, image = TRUE, contour = TRUE, swap = TRUE)
plot3d(f, image = TRUE, contour = TRUE, col.contour = "white")
plot3d(f, contour = TRUE)
op <- par(no.readonly = TRUE)
par(mfrow = c(1, 3))
plot3d(f, image = TRUE, contour = TRUE, c.select = 3)
plot3d(f, image = TRUE, contour = TRUE, c.select = "Estimate")
plot3d(f, image = TRUE, contour = TRUE, c.select = "97.5par(op)

## another variation
dat$f1 <- with(dat, sin(z) * cos(w))
plot3d(cbind(z = dat$z, w = dat$w, f1 = dat$f1))

## same with formula 
plot3d(sin(z) * cos(w) ~ z + w, zlab = "f(z,w)", data = dat)
plot3d(sin(z) * cos(w) ~ z + w, zlab = "f(z,w)", data = dat, 
  ticktype = "detailed")

## play with palettes
plot3d(sin(z) * cos(w) ~ z + w, col.surface = heat.colors, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = topo.colors, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = cm.colors, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = rainbow, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = terrain.colors, data = dat)

plot3d(sin(z) * cos(w) ~ z + w, col.surface = rainbow_hcl, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = diverge_hcl, data = dat)
plot3d(sin(z) * cos(w) ~ z + w, col.surface = sequential_hcl, data = dat)

plot3d(sin(z) * cos(w) ~ z + w, 
  col.surface = rainbow_hcl(n = 99, c = 300, l = 80, start = 0, end = 100), 
  data = dat)
plot3d(sin(z) * cos(w) ~ z + w, 
  col.surface = rainbow_hcl(n = 99, c = 300, l = 80, start = 0, end = 100), 
  image = TRUE, grid = 200, data = dat)