similar to: help in md scaling

Displaying 20 results from an estimated 90000 matches similar to: "help in md scaling"

2007 Nov 28
0
qestion on cmd scale
Dear list, I am starting a new project in cmdscale, and I have a question regarding distance matrix and covariance matrix. Can anyone help me in this? I sent this message so many times but always bounced with no further explanation. (1) Can I use covariance as my distance matrix? (2) Any good reference in this matter? (3) is the approach that I wrote below valid? Thank you, ilham Below is what
2004 Feb 26
2
Multidimensional scaling and distance matrices
Dear All, I am in the somewhat unfortunate position of having to reproduce the results previously obtained from (non-metric?) MDS on a "kinship" matrix using Statistica. A kinship matrix measures affinity between groups, and has its maximum values on the diagonal. Apparently, starting with a nxn kinship matrix, all it was needed to do was to feed it to Statistica flagging that the
2007 Nov 24
3
help in plotting
Dear list, I want to combine several plots in one graph. I did this: plot(a1); plot(a2, add=TRUE); ...plot(a5, add=TRUE) The problem is the more plot we put, the more complex the graph. Is there any way to label each line; or other way just to make sure I know which one which? Thank you for the help, Ilham [[alternative HTML version deleted]]
2005 May 12
0
Multidimensional Scaling with pairwise Fst
I want to create a MDS plot with pairwise Fst values derived from a population genetics project. My Fst values are in a tab-delimited file (lower triangle only) that I view with Excel. When I use the cmdscale command I get the message: Error in cmdscale(x) : Distances must be result of dist or a square matrix In addition: Warning messages: 1: "^" not meaningful for factors in:
1999 Oct 10
1
Using metric scaling
I want to enter a symmetric matrix containing distances for use in the cmdscale() metric scaling function. The matrix currently sits on a file in lower triangular form looking like this: 1 AWANUI RIVER .000 2 BLENHEIM .510 .000 3 COLLINGWOOD .510 .109 .000 4 FOXTON .510 .141 .141 .000 5 GISBORNE .549 .549 .549
2007 Nov 21
1
Calculating AUC from ROCR
Dear R-helper, I am working with ROCR of Tobias Sing et. al. to compare the performances of logistic and nnet models on a binary response. I had the performance plots, but I have problem finding out other performance statistics (eg. MSE/ASE, AUC). Any help on this? Thanks Ilham [[alternative HTML version deleted]]
2005 Jun 28
1
enhanced multidimensional scaling?
Dear R list Would anyone be able to tell me whether it is possible to do "enhanced multidimensional scaling" (enhanced MDS) in R? In other words, something that goes beyond "cmdscale" by iteratively improving the fit between observed dissimilarities and inter-object distances, using the KYST algorithm (Kruskal, 1964). I have found several implementations of non-metric MDS
2005 Jan 08
0
cmdscale problem
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
1999 Oct 07
1
[Fwd: Libraries loading, but not really?] - it really IS a problem :-(
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
2003 Oct 07
0
NaN values returned by cmdscale
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
2005 Nov 04
1
Stress in multidimensional scaling
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
2013 Apr 09
0
How does clusplot exactly make use of cmdscale?
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.
2011 Feb 14
1
Analyzing dissimilarity ratings with Multidimensional Scaling
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
2011 Apr 02
3
Plotting MDS (multidimensional scaling)
Hi, I just encountered what I thought was strange behavior in MDS. However, it turned out that the mistake was mine. The lesson learned from my mistake is that one should plot on a square pane when plotting results of an MDS. Not doing so can be very misleading. Follow the example of an equilateral triangle below to see what I mean. I hope this helps others to avoid this kind of headache.
2016 Apr 25
1
how to create initial configuraton for isoMDS
Hi, I'm trying to use isoMDS to project a directed graph to 2-dim vectors, but I got an error. #here is the code to create the graph using igraph package and run isoMDS on it. library(igraph) library(MASS) g<-make_graph(c(1,2, 2,3, 2,4, 3,4, 4,5, 5,6, 3,6, 1,6, 2,5),directed=TRUE) dist<-distances(g, mode="out") loc<-isoMDS(dist) # below is content of the dist matrix
2012 Feb 23
2
Advice on exploration of sub-clusters in hierarchical dendrogram
Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of
2002 Feb 15
1
cmdscale k=1
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
2002 Dec 19
1
newbie question on dist
hi, i have just begun using R, so please bear with me. i am trying to use cmdscale and display the result. i read the data using read.table(), calculate the proximity matrix using dist() and the display the result using the cmdscale(). this is very fine. in addition, i want the display to distinguish between two classes of records in my data. i have my data records marked as "1" or
2007 Jun 14
2
Difference between prcomp and cmdscale
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) <-
2008 Feb 20
1
Stress with MDS
Hi, I am looking for the best multidimensional configuration for my data (47*47 distance matrix). I ve tried classical metric (cmdscale) and non metric MDS (isoMDS, nmds) but it is now difficult to choose the best solution because of the uncertainties in the definitions of the "stress" function. So, same problem, several questions : 1. Statistical consideration : With