Function to plot effects for model terms including factor, or group variables for random effects,
typically used for objects created within bayesx or read.bayesx.output.
either a list of length of the unique factors, where each list element
contains the estimated effects for one factor as a matrix, see fitted.bayesx, or
one data matrix with first column as the group or factor variable. Also formulas are accepted,
e.g it is possible to specify the plot with f ~ x or f1 + f2 ~ x. By convention,
the covariate for which effects should be plotted, is always in the first column in the
resulting data matrix, that is used for plotting, i.e. in the second formula example, the data
matrix is cbind(x, f1, f2), also see argument c.select and fill.select.
residuals
if set to TRUE, partial residuals will be plotted if available. Partial
residuals may be set as an attribute of x named
"partial.resids", where the partial residuals must be a matrix with first column
specifying the covariate, and second column the partial residuals that should be plotted.
range
numeric vector, specifying the left and right bound of the block.
col.residuals
the color of the partial residuals.
col.lines
vector of maximum length of columns of x minus 1, specifying the color of
the 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 select column 1, 2 and 5 for plotting. Note that
first element of c.select should always be 1, since this is the column of the covariate
the effect is plotted for.
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 col.
E.g. x has three columns, or is specified with formula f1 + f2 ~ x, then setting
fill.select = c(0, 1, 1) will draw a polygon with f1 and f2 as boundaries.
If x has five columns or the formula is e.g. f1 + f2 + f3 + f4 ~ x, then setting
fill.select = c(0, 1, 1, 2, 2), the pairs f1, f2 and f3, f4
are selected to form two polygons.
col.polygons
specify the background color for the upper and lower confidence bands, e.g.
col = c("green", "red").
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 plotblock is
called.
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.
...
graphical parameters, please see the details.
Details
Function plotblock draws for every factor or group the effect as a "block" in one graphic,
i.e. similar to boxplots, estimated fitted effects, e.g. containing quantiles for MCMC
estimated models, are drawn as one block, where the upper lines represent upper quantiles, the
middle line the mean or median, and lower lines lower quantiles, also see the examples. The
following graphical parameters may be supplied 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,
densityangle, border: see polygon,
...: other graphical parameters, see function plot.
Author(s)
Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.