MDS {MVar} | R Documentation |
Performs Multidimensional Scaling (MDS) on a data set.
MDS(data, distance = "euclidean", title = NA, xlabel = NA, ylabel = NA, posleg = 2, boxleg = TRUE, axes = TRUE, size = 1.1, grid = TRUE, color = TRUE, linlab = NA, class = NA)
data |
Data to be analyzed. |
distance |
Metric of the distance: "euclidean" (default), "maximum", "manhattan", "canberra", "binary" or "minkowski". |
title |
Titles of the graphics, if not set, assumes the default text. |
xlabel |
Names the X axis, if not set, assumes the default text. |
ylabel |
Names the Y axis, if not set, assumes the default text. |
posleg |
0 with no caption, |
boxleg |
Puts the frame in the caption (default = TRUE). |
axes |
Plot the X and Y axes (default = TRUE). |
size |
Size of the points in the graphs. |
grid |
Put grid on graphs (default = TRUE). |
color |
Colored graphics (default = TRUE). |
linlab |
Vector with the labels for the observations. |
class |
Vector with names of data classes. |
Multidimensional Scaling.
mtxD |
Matrix of the distances. |
Paulo Cesar Ossani
Marcelo Angelo Cirillo
MINGOTI, S. A. Analise de dados atraves de metodos de estatistica multivariada: uma abordagem aplicada. Belo Horizonte: UFMG, 2005. 297 p.
RENCHER, A. C. Methods of multivariate analysis. 2th. ed. New York: J.Wiley, 2002. 708 p.
data(iris) # data set data <- iris[,1:4] cls <- iris[,5] # data class MD <- MDS(data = data, distance = "euclidean", title = NA, xlabel = NA, ylabel = NA, posleg = 2, boxleg = TRUE, axes = TRUE, color = TRUE, linlab = NA, class = cls) print("Matrix of the distances:"); MD$mtxD