plot-methods {rebmix} | R Documentation |
Plots true clusters if x
equals "RNGMIX"
. Plots the REBMIX output
depending on what
argument if x
equals "REBMIX"
.
Plots predictive clusters if x
equals "RCLRMIX"
.
Wrongly clustered observations are plotted only if x@Zt
is available.
Plots predictive classes and wrongly classified observations if x
equals "RCLSMIX"
.
## S4 method for signature 'RNGMIX,missing' plot(x, y, pos = 1, nrow = 1, ncol = 1, cex = 0.8, fg = "black", lty = "solid", lwd = 1, pty = "m", tcl = 0.5, plot.cex = 0.8, plot.pch = 19, ...) ## S4 method for signature 'REBMIX,missing' plot(x, y, pos = 1, what = c("density"), nrow = 1, ncol = 1, npts = 200, n = 200, cex = 0.8, fg = "black", lty = "solid", lwd = 1, pty = "m", tcl = 0.5, plot.cex = 0.8, plot.pch = 19, contour.drawlabels = FALSE, contour.labcex = 0.8, contour.method = "flattest", contour.nlevels = 12, ...) ## S4 method for signature 'RCLRMIX,missing' plot(x, y, s = expression(c), nrow = 1, ncol = 1, cex = 0.8, fg = "black", lty = "solid", lwd = 1, pty = "m", tcl = 0.5, plot.cex = 0.8, plot.pch = 19, ...) ## S4 method for signature 'RCLSMIX,missing' plot(x, y, nrow = 1, ncol = 1, cex = 0.8, fg = "black", lty = "solid", lwd = 1, pty = "m", tcl = 0.5, plot.cex = 0.8, plot.pch = 19, ...) ## ... and for other signatures
x |
see Methods section below. |
y |
currently not used. |
pos |
a desired row number in |
s |
a desired number of clusters to be plotted. The default value is |
what |
a character vector giving the plot types. One of |
nrow |
a desired number of rows in which the empirical and predictive densities are to be plotted. The default value is |
ncol |
a desired number of columns in which the empirical and predictive densities are to be plotted. The default value is |
npts |
a number of points at which the predictive densities are to be plotted. The default value is |
n |
a number of observations to be plotted. The default value is |
cex |
a numerical value giving the amount by which the plotting text and symbols should be magnified
relative to the default, see also |
fg |
a colour used for things like axes and boxes around plots, see also |
lty |
a line type, see also |
lwd |
a line width, see also |
pty |
a character specifying the type of the plot region to be used. One of |
tcl |
a length of tick marks as a fraction of the height of a line of the text, see also |
plot.cex |
a numerical vector giving the amount by which plotting characters and symbols should be
scaled relative to the default. It works as a multiple of |
plot.pch |
a vector of plotting characters or symbols, see also |
contour.drawlabels |
logical. The contours are labelled if |
contour.labcex |
|
contour.method |
a character specifying where the labels will be located. The possible values
are |
contour.nlevels |
a number of desired contour levels. The default value is |
... |
further arguments to |
Returns (invisibly) a list containing graphical parameters par
. Such a list can be passed as an argument to par
to restore the parameter values.
signature(x = "RNGMIX", y = "missing")
an object of class RNGMIX
.
signature(x = "RNGMVNORM", y = "missing")
an object of class RNGMVNORM
.
signature(x = "REBMIX", y = "missing")
an object of class REBMIX
.
signature(x = "REBMVNORM", y = "missing")
an object of class REBMVNORM
.
signature(x = "RCLRMIX", y = "missing")
an object of class RCLRMIX
.
signature(x = "RCLRMVNORM", y = "missing")
an object of class RCLRMVNORM
.
signature(x = "RCLSMIX", y = "missing")
an object of class RCLSMIX
.
signature(x = "RCLSMVNORM", y = "missing")
an object of class RCLSMVNORM
.
Marko Nagode
C. M. Bishop. Neural Networks for Pattern Recognition. Clarendon Press, Oxford, 1995.
## Not run: devAskNewPage(ask = TRUE) data("wine") colnames(wine) # Remove Cultivar column from wine dataset. winecolnames <- !(colnames(wine) %in% "Cultivar") wine <- wine[, winecolnames] # Determine number of dimensions d and wine dataset size n. d <- ncol(wine) n <- nrow(wine) # Estimate number of components, component weights and component parameters. Sturges <- as.integer(1 + log2(n)) # Minimum v follows Sturges rule. RootN <- as.integer(2 * n^0.5) # Maximum v follows RootN rule. K <- c(floor(Sturges^(1/13)), ceiling(RootN^(1/13))) wineest <- REBMIX(model = "REBMVNORM", Dataset = list(wine = wine), Preprocessing = "kernel density estimation", Criterion = "ICL-BIC", pdf = rep("normal", d), K = K[1]:K[2]) # Plot finite mixture. plot(wineest, what = c("density", "IC", "logL", "D"), nrow = 2, ncol = 2, pty = "s") ## End(Not run)