plot method for class "LogConcDEAD". Plots of various
types are available for 1- and 2-d data. For dimension greater than 1,
plots of axis-aligned marginal density estimates are available.## S3 method for class 'LogConcDEAD':
plot(x, uselog=FALSE, type="ic", addp=TRUE,
drawlabels=TRUE, gridlen=100, g, marg, g.marg, main, xlab, ylab, ...)"LogConcDEAD" (typically output from mlelcd)logical: should the plot be on the log scale?"p" perspective, "c" contour, "i" image, ic
image and contour, r using logical: should the data points be plotted? (On the surface for $d \geq 2$; as tick marks for $d=1$)logical: should labels be added to
contour lines? (only relevant for types "ic" and "c")matrix of density estimate values (the result of a call to interplcd). If many plots of a single dataset are
required, it may be quicker to compute the grid using
NULL, this scalar integer determines which marginal should be
plotted (should be between $1$ and $d$)g is non-NULL, can contain a
vector of marginal density estimate values (the output of interpmarglcd). If many plots of a single dataset
are required, itplot methodinterplcd function. If several plots are required, this
may be computed separately and passed to plot using the
g argument.
For two dimensional data, the default plot type is "ic",
corresponding to image and contour plots.
These may be obtained separately using plot type "i" or "c"
respectively. Where available, the use of plot type "r" is
recommended. This uses the "p" produces perspective plots.
For data of dimension at least 2, axis-aligned marginals may be
plotted by setting the marg argument. This integrates the
estimated density over the remaining dimensions. If several plots are
required, the estimate may be computed using the function
interpmarglcd and passed using the argument
g.marg. Where relevant, the colors were obtained from the function
heat_hcl in the package
For examples, see mlelcd.
mlelcd, interplcd, interpmarglcd, heat_hcl