plot2d {bamlss}  R Documentation 
Function to plot simple 2D graphics for univariate effects/functions.
plot2d(x, residuals = FALSE, rug = FALSE, jitter = TRUE, col.residuals = NULL, col.lines = NULL, col.polygons = NULL, col.rug = NULL, c.select = NULL, fill.select = NULL, data = NULL, sep = "", month = NULL, year = NULL, step = 12, shift = NULL, trans = NULL, scheme = 2, s2.col = NULL, grid = 50, ...)
x 
A matrix or data frame, containing the covariate for which the effect should be plotted
in the first column and at least a second column containing the effect. Another possibility is
to specify the plot via a 
residuals 
If set to 
rug 
Add a 
jitter 

col.residuals 
The color of the partial residuals. 
col.lines 
The color of the lines. 
col.polygons 
Specify the background color of polygons, if 
col.rug 
Specify the color of the rug representation. 
c.select 
Integer vector of maximum length of columns of 
fill.select 
Integer vector, select pairwise the columns of the resulting data matrix
that should form one polygon with a certain background color specified in argument 
data 
If 
sep 
The field separator character when 
month, year, step 
Provide specific annotation for plotting estimation results for temporal
variables. 
shift 
Numeric constant to be added to the smooth before plotting. 
trans 
Function to be applied to the smooth before plotting, e.g., to transform the plot to the response scale. 
scheme 
Sets the plotting scheme for polygons, possible values are 
s2.col 
The color for the second plotting scheme. 
grid 
Integer, specifies the number of polygons for the second plotting scheme. 
... 
Other graphical parameters, please see the details. 
For 2D plots the following graphical parameters may be specified additionally:
cex
: Specify the size of partial residuals,
lty
: The line type for each column that is plotted, e.g. lty = c(1, 2)
,
lwd
: The line width for each column that is plotted, e.g. lwd = c(1, 2)
,
poly.lty
: The line type to be used for the polygons,
poly.lwd
: The line width to be used for the polygons,
density
angle
, border
: See polygon
,
...
: Other graphical parameters, see function plot
.
plot3d
, plotmap
,
plotblock
, sliceplot
.
## Generate some data. set.seed(111) n < 500 ## Regressor. d < data.frame(x = runif(n, 3, 3)) ## Response. d$y < with(d, 10 + sin(x) + rnorm(n, sd = 0.6)) ## Not run: ## Estimate model. b < bamlss(y ~ s(x), data = d) summary(b) ## Plot estimated effect. plot(b) plot(b, rug = FALSE) ## Extract fitted values. f < fitted(b, model = "mu", term = "s(x)") f < cbind(d["x"], f) ## Now use plot2d. plot2d(f) plot2d(f, fill.select = c(0, 1, 0, 1)) plot2d(f, fill.select = c(0, 1, 0, 1), lty = c(2, 1, 2)) plot2d(f, fill.select = c(0, 1, 0, 1), lty = c(2, 1, 2), scheme = 2) ## Variations. plot2d(sin(x) ~ x, data = d) d$f < with(d, sin(d$x)) plot2d(f ~ x, data = d) d$f1 < with(d, f + 0.1) d$f2 < with(d, f  0.1) plot2d(f1 + f2 ~ x, data = d) plot2d(f1 + f2 ~ x, data = d, fill.select = c(0, 1, 1), lty = 0) plot2d(f1 + f2 ~ x, data = d, fill.select = c(0, 1, 1), lty = 0, density = 20, poly.lty = 1, poly.lwd = 2) plot2d(f1 + f + f2 ~ x, data = d, fill.select = c(0, 1, 0, 1), lty = c(0, 1, 0), density = 20, poly.lty = 1, poly.lwd = 2) ## End(Not run)