similar to: kruskal's MONANOVA algorithm

Hi, I am trying to use R to mimic what I did in SAS. proc transreg data=x ; model identity(GSI)=monotone(group1); output out=d2 pprefix=M; run; Accroding to SAS documentation, the MONOTONE transfomation algorithm comes from (Kruskal 1964, secondary approach to ties). I have tried ace. it does provide some kind of monotone transformation, but it is not what I expected. Here is how

Hi I need to know which package in R calculates the Goodman Kruskal's tau statistic for nominal data. Also is there any implementation for multiple classification analysis (Andrews at al 1973) in R? Any information on this would be greatly appreciated. Thank you Upasna -- --------------------------------------------------------------------- Upasna Sharma Research Scholar Shailesh J. Mehta

Dear List, I'm trying to interpret the results of the Kruskal's Non-metric Multidimensional Scaling algorithm (isoMDS, MASS package). The 'goodness of fit' is reported as "The final stress achieved (in percent)". What does this mean exactly? I've tried to google for an answer but I've not come up with a definitive answer. Regards, Dieter -- Dieter Vanderelst

Hi All, My paper "R for SAS and SPSS Users" received a bit more of a reaction than I expected. I posted the link (http://oit.utk.edu/scc/RforSAS&SPSSusers.pdf) about 12 days ago on R-help and the equivalent SAS and SPSS lists. Since then people have downloaded it 5,503 times and I've gotten lots of questions along the lines of, "Surely R can't do for free what [fill in

Thank you so much Dr. Nash, I truly appreciate your kind and valuable contribution. Cheers, Paul El El s?b, 19 de ago. de 2023 a la(s) 3:35 p. m., J C Nash < profjcnash at gmail.com> escribi?: > Why bother. nlsr can find a solution from very crude start. > > Mixture <- c(17, 14, 5, 1, 11, 2, 16, 7, 19, 23, 20, 6, 13, 21, 3, 18, 15, > 26, 8, 22) > x1 <- c(69.98, 72.5,

The cautions people have given about starting values are worth heeding. That nlxb() does well in many cases is useful, but not foolproof. And John Fox has shown that the problem can be tackled very simply too. Best, JN On 2023-08-19 18:42, Paul Bernal wrote: > Thank you so much Dr. Nash, I truly appreciate your kind and valuable contribution. > > Cheers, > Paul > > El El

Dear friends, Hope you are all doing well and having a great weekend. I have data that was collected on specific gravity and spectrophotometer analysis for 26 mixtures of NG (nitroglycerine), TA (triacetin), and 2 NDPA (2 - nitrodiphenylamine). In the dataset, x1 = %NG, x2 = %TA, and x3 = %2 NDPA. The response variable is the specific gravity, and the rest of the variables are the predictors.

I have a full data set like this: aa bas aas bms ams bcu acu omega y 1 ALA 0 127.71 0 69.99 0 -0.2498560 79.91470 outward 2 PRO 0 68.55 0 55.44 0 -0.0949008 76.60380 outward 3 ALA 0 52.72 0 47.82 0 -0.0396550 52.19970 outward 4 PHE 0 22.62 0 31.21 0 0.1270330 169.52500 inward 5 SER 0 71.32 0 52.84 0 -0.1312380 7.47528 outward 6

I will be out of the office starting 12/07/2007 and will not return until 12/10/2007. I will reply to your message when I return Monday, December 10th. For MSRB / TRACE / OATS or Partnerships/Scorecard issues please call the Trade Reporting Control main number: 804-344-6216. For issues requiring escalation please contact Ralph Brugueras: 804-344-6515. Thank you. The information is not

I will be out of the office starting 02/22/2008 and will not return until 02/25/2008. I will reply to your message when I return Monday, February 25th. For MSRB / TRACE / OATS issues please call the Trade Reporting Control main number: 804-344-6216. For issues requiring escalation please contact Ralph Brugueras: 804-344-6515. Thank you. ATTENTION: Please be aware that since the

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Dear useRs, last week I asked you about a problem related to isoMDS. It turned out that in my case isoMDS was trapped. Nonetheless, I still have some problems with other data sets. Therefore I would like to know if anyone here has experience with how well isoMDS performs in comparison to other non-metric MDS routines, like Minissa. I have the feeling that for large data sets with a high

On Wed, 1 Aug 2007, Upasna Sharma <upasna at iitb.ac.in> wrote: > From: "Upasna Sharma" <upasna at iitb.ac.in> > Subject: [R] Goodman Kruskal's tau > > I need to know which package in R calculates the Goodman Kruskal's > tau statistic for nominal data. Also is there any implementation for > multiple classification analysis (Andrews at al 1973) in R?

Full_Name: Greg Kochanski Version: 2.2.1 OS: Debian Linux (testing) Submission from: (NULL) (212.159.16.190) This is really a feature request. When you do mosaicplot() on a data set where the probability of several nearby rows is small, then the labels for those rows are plotted overlapping each other. This situation can be improved by calling mosaicplot() with a large value of

Hi all, I am a real novice to R. :) I am struggling with a problem for generating colored dendrogram. I have searched the R list and complied/collected a R code which can generated a colored dendrogram based on the rainbow color and 4x4 similarity matrix (say matrix:m). In this dendrogram, each leaf is colored differently. But, I do not want the leaf colored on a random basis. I want to assign

Dear All, This is not strictly R related (though I would implement the solution in R; besides, being this list so helpful for these kinds of stats questions...). I got a "strange" request from a colleage. He has a bunch (approx. 25000) subjects that belong to one of 12 possible classes. In addition, there are 8 covariates (factors) that can take as values either "absence"

I sent a query to R-Help about the availability of nonmetric multidimensional scaling (MDS) algorithms in R. I would like to thank Tony Rossini, Jonathan Baron, Sundar Dorai-Raj, and Brian Ripley for helpful replies. The gist of the replies is that isoMDS in the MASS library provides Kruskal's method for nonmetric MDS, sammon in the MASS library provides Sammon's nonlinear mapping method

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

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

[2017/09/28 03:46:51.256663, 1] ../source4/dsdb/kcc/kcc_topology.c:2730(kcctpl_get_spanning_tree_edges) ../source4/dsdb/kcc/kcc_topology.c:2730: failed to run Kruskal's algorithm: NT_STATUS_INVALID_PARAMETER [2017/09/28 03:46:51.256953, 1] ../source4/dsdb/kcc/kcc_topology.c:3283(kcctpl_create_connections) ../source4/dsdb/kcc/kcc_topology.c:3283: failed get spanning tree edges: