Nothing
"plot.LCcluster" <-
function (x, ...)
{
if (x$method == "diana")
plot(x$hclus, main = "Diana Divisive Dendrogram",
sub = paste("Divisive Coefficient = ", round(x$hclus$dc,
digits = 2)))
else
plot(x$hclus, main = paste( x$method, "Agglomerative Dendrogram"))
}
"print.LCcluster" <-
function (x, ...)
{
cat("\n\nLCcluster object: Hierarchical Clustering for LC\n")
cat("\nData Frame input:", x$dframe)
if( x$method == "diana" ) cat("\nClustering algorithm used: diana")
cat("\nCovariate X variables:")
print(x$xvars, quote = FALSE)
if( x$method != "diana" ) print(x$hclus)
else cat("\nDivisive Coefficient = ", round(x$hclus$dc, digits = 2), "\n\n")
}
"LCcluster" <-
function (dframe, xvars, method = "ward.D")
{
if (missing(dframe) || !inherits(dframe, "data.frame"))
stop("First argument to LCcluster() must be an existing data.frame name.")
if (missing(xvars))
stop("Second argument to LCcluster() must be a list of X variables.")
# Center and Rotate X-coordinates of Experimental Units...
xpc <- prcomp(dframe[, xvars], scale. = TRUE, rank. = length(xvars))
# Calculate Mahalanobis Coordinates...
for ( i in 1:length(xvars)) {
z = xpc$x[,i] / xpc$sdev[i]
if ( i == 1 )
xmat = z
else
xmat = cbind( xmat, z )
}
dim(xmat) <- c(length(z),length(xvars))
if (method == "diana") {
hclus <- diana(dist(xmat), metric = "euclidean",
stand = TRUE, keep.diss = FALSE, keep.data = FALSE)
}
else {
hclus <- hclust(dist(xmat), method = method)
}
dframe <- deparse(substitute(dframe))
olist <- list(dframe = dframe, xvars = xvars, method = method,
hclus = hclus)
class(olist) <- "LCcluster"
olist
}
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