similar to: prcomp( and cmdscale( not equivalent?

I'm looking for someone to explain the difference between these procedures. The function prcomp() does principal components anaylsis, and the function cmdscale() does classical multi-dimensional scaling (also called principal coordinates analysis). My confusion stems from the fact that they give very similar results: my.d <- matrix(rnorm(50), ncol=5) rownames(my.d) <-

I have a dataframe like this (toy example): x y z "a" "a" 0 "a" "b" 1 "a" "c" 2 "b" "a" .9 "b" "b" 0 "b" "c" 1.3 "c" "a" 2.2 "c" "b" 1.1 "c" "c" 0 The observations are from a matrix like this: c 2.2 1.1 0.0 b 0.9 0.0

Dear R-list members, I need an help with the Multidimensional Scaling analysis (MDS). So far I used the cmdscale() command in R, but I did not get the perceptual map I would love to see, and I would like to know if it is possible to get it using R, and if yes how. I also had a look to the functions isoMDS() and sammoc() but with no luck. I summarize the experiment I performed, and I would ask you

Dear R developers, there appears to be a small problem with function cmdscale: for non-Euclidean distance matrices, using option add=FALSE (the default), cmdscale misses the smallest eigenvalue. This affects GOF statistic g.1 (See Mardia, Kent + Bibby (1979): Multivariate Analysis, eq. (14.4.7). The corresponding formula in Cox + Cox (2001): Multidimensional Scaling, 2nd ed., p 38, would

In applying multidimensional scaling, it seems to me that sometimes the underlying dimensionality of the matrix is 1. However I found a case where cmdscale failed when I tried k=1. Here it is: m<-matrix( c(.5,.81,.23,.47,.61, .19,.5,.06,.17,.28, .77,.94,.5,.74,.85, .53,.83,.26,.5,.64, .39,.72,.15,.36,.5), nrow=5) # BTW I think cmdscale uses only the lower triangle--how to enter only # that

Hi We have a few questions regarding the use of the "isoMDS" function. When we run "isoMDS" function using 60,000 x 60,000 data matrix, we get the following error message: ------------------------------------ cmdscale(d, k) : invalid value of 'n' Calls: isoMDS -> cmdscale ------------------------------------ We checked the source code of "cmdscale" and

Hello all, I'm using R1.7.1 on Linux, generating sammon-optimized MDS plots from distance matrices. This is a calculation I run routinely, often on sample sets of up to 100 samples. This time, with three samples, the sammon function returned an error (shown below), which I tracked down to the cmdscale function it uses to find a starting configuration. In short, cmdscale is returning NaN

kalish at psy.uwa.edu.au wrote: > > I'm a newbie at R, and can't get libraries to really work. > I did this: > > library(help = mva) > cancor Canonical Correlations > cmdscale Classical (Metric) Multidimensional Scaling > dist Distance Matrix Computation > hclust Hierarchical Clustering

Hi. I know matrices that use distances between places works fine when using cmdscale. However, what about matricies such as: A B C D E A 0 1 23 12 9 B 1 0 10 12 3 C 23 10 0 23 4 D 12 12 23 0 21 E 9 3 4 21 0 i.e. matrices which do not represent physical distances between places (as they would not make sense for real distances such as the one above)

Full_Name: Laurent Gautier Version: 1.3.0-patched OS: IRIX 6.5 Submission from: (NULL) (130.225.67.199) Hello, The function La.eigen, called by cmdscale in the package mva behaves an unexplicable way (for me). The following lines show what happened. I tried the very same on linux, and it worked fine. >a <- matrix(c(1,2,3,2),3,3) >a [,1] [,2] [,3] [1,] 1 2 3 [2,]

Hello, We are trying to find a function to compute "stress" in our multidimensional scaling analysis of a dissimilarity matrix. We've used "dist()" to create the matrix and "cmdscale()" for the scaling. In order to determine the number of dimensions we would like to plot stress vs. dimensions. However, we cannot find a pre-made command. It seems that other

The following problem occurs in R 1.4.0 and 1.3.1 for Windows95, but not in R 1.2.0 for Windows95. The problem does not occur in R 1.4.0 for Linux PC, Linux Alpha and HP-UX. Sometimes, the type of 'Size' of an object of type 'dist' changes from integer into double. Running cmdscale on such a 'dist' object gives invalid results. I don't know what should be considered

The following code in clusplot.default (package cluster) is in error: x1 <- cmdscale(x, k = 2, eig = TRUE) var.dec <- sum(x1$eig)/sum(diag(x1$x)) if (var.dec < 0) var.dec <- 0 if (var.dec > 1) var.dec <- 1 x1 <- x1$points x1 has components with names "points" and "eig", not "x", so

Hello everyone, this is my first post here and I hope I signed up correctly and someone will take me by the hand and help me out. I am new to R and cannot figure out what to do here... ... I want to have an User Interface that requests input. I want to save this input to a variable to use it later on. I was able to do this with a modalDiaglog (

I'm relatively new to R and I'm stuck. I'm trying to construct a surface to optimize from a multivariate dataset. The dataset contains the response of a system to various stimuli. I am trying to optimize the mix of stimuli to maximize the response. To do so, I've interpolated the various datasets of type response vs. stimuli and I now have an array of functions

Hello I am using the following command but not able to text the values on the graph can someone please make suggestions for improvement #here is the command loc_mds <- cmdscale(dist.r, k = 7, eig = TRUE) loc_mds$eig sum(abs(loc_mds$eig[1:2]))/sum(abs(loc_mds$eig)) sum((loc_mds$eig[1:2])^2)/sum((loc_mds$eig)^2) x <-loc_mds$points[,1] y <-loc_mds$points[,2] plot(x, y,

The function cmdscale tries to copy names from the source to the result. This only works if the source is a matrix. If m is a matrix with labels (rownames) and d is an object of class "dist" with labels, this works: cmdscale(m) ...but with this, there are no labels in the results: cmdscale(d) However, this works: cmdscale(as.matrix(d)) My suggestion is to change, in

Dear people, I used clusplot to plot a partition result. The partition result was from pamk with a distance object as input. Then I applied cmdscale on the same distance object for coordinates to make another scatterplot. My problem is this: the coordinates from the cmdscale calculation, though with the same shape, were different in scale and rotation from the scatter plot yielded by clusplot.

Full_Name: Cam Webb Version: 1.6.0 (fink X11 compile) OS: Mac OS X (Jaguar) Submission from: (NULL) (64.168.28.87) This is an unpredictable, intermittant hang during cmdscale of the mva library. Some data never cause a problem, other data always do, abut I can't track down the difference in the structure of the data. Sometimes the function will work for `difficult' data after it has

Dear all, how can I perform a post hoc analysis for ANOVA with repeated measures (in presence of a balanced design)? I am not able to find a good example over internet in R...is there among you someone so kind to give me an hint with a R example please? For example, the aov result of my analysis says that there is a statistical difference between stimuli (there are 7 different stimuli). ...I