search for: scree

hello, I've two questions today. 1) I'm trying to do a scree diagram, I did a Google for a specific command I could used to do so. All I could find is a screeplot. Are they the same command? 2) what command can I used to present a PC scores, eigenvectors of the PC scores, and component correlations? thanks! -- View this message in context: http://r.7896...

Hi! Is there an easy way to add to the scree-plot labels to each value pertaining to the cumulative proportion of explained variance? Thanks and a happy new year Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com ---------------------------------------------------...

...nal." [Hogenraad, R., & McKenzie, DP (1999). Replicating text: The cumulation of knowledge in social science. Quality & Quantity, 33:2, 97-116] Could anyone advise me whether (and how) it is possible to undertake a similar analysis in R? Q.2) Has anyone implemented the Standard Error Scree or a similar objective procedure for determining the optimal number of factors? Many thanks, Andrew Wilson

Hello, I am using function princomp from the package psych. I have my principle component object mypc: mypc <- princomp(covmat=mycor) plot(mypc) # shows me a screeplot Question: how could I actually see the values displayed in the screeplot. I don't mean on the graph - I just want to know the actual value for each component (e.g., 10, 3.2, 1.8, etc.) I need to know how much variance, in total, a certain number of comonents explain. Thanks a lot! --...

...is. It is annoying because they will be marking to the SPSS output. Basically I'm getting different values for the component loadings in SPSS and in R - I suspect that there is some normalization or scaling going on that I don't understand (and there is plenty I don't understand). The scree-plots (and thus eigen values for each component) and Proportion of Variance figures are identical - but the factor loadings are an order of magnitude different. Basically the SPSS loadings are much higher than those shown by R. Should the loadings returned by the R princomp function and the SPSS...

Hello! Very often one can hear that MDS usually ends with two-dimensional solution. Of course, there are methods, like Scree-test (proposed by Kruskal and Wish, 1981), to determine optimal number of dimensions. However, I am trying to find references to this two-dimensional gold-standard. Can anyone point me to authors which explicitly states that two-dimensions are typical and easiest to represent graphically? In B...

...ome more work. It should only apply to decorated toplevels, but right now it also affects XUL menus (I guess because they are not unmanaged like in GTK?). It also affects the tab switcher window, which looks OK but a bit _too_ distracting IMHO. And finally sometimes visual artifacts are left on scree, though this may be simply my video drivers (nvidia binary geforce4 mx 440). Author unknown. Credit Quinn Storm. -------------- next part -------------- A non-text attachment was scrubbed... Name: minimize-scaler-mod.patch Type: text/x-patch Size: 8940 bytes Desc: not available Url : http://list...

Dear all I have two 10*10 matrixes and I would like to compare theirs contents. By the word content I mean to check visually (not with any mathematical formulation) how similar are the contents. I also know edit that prints my matrix in the scree but still one edit blocks the prompt to launch a second edit() screen. What is the best way to compare these two matrices? I would like to thank you in avdance for your help Regards Alex

...t kidding about obscure syntax, sipsak is a PITA -----Original Message----- From: Sean Kennedy [mailto:skennedy@qualitydentists.com] Sent: Thursday, March 09, 2006 5:01 PM To: Asterisk Users Mailing List - Non-Commercial Discussion Subject: Re: [Asterisk-Users] OT: Snom 320, displaying text on the screen from * I have that set, but for some reason I get errors when I try sipsak, and nothing comes through to the phone: sipsak -M -B "test" -s sip:44@192.168.1.67 <sip:44@192.168.1.67> timeout after 500ms timeout after 500ms... Some debugging info: [root@firewall root]# sipsa...

I am a newcomer to R trying to convert a SAS program to R. Does anyone know if there is a functional equivalent of the SAS 'Factor' procedure? For example in SAS: proc factor DATA=cor method=principal rotate=varimax proportion=0.9 scree where 'cor' is a correlation matrix (as in the R 'cor' function) This should get you a list of eigen values as well as a factor pattern matrix. Also why when I use the 'eigen' function in R does it seem to give a subtly different answer to the eigen values generated by th...

Hi there! To make a good choice for the estimation of the number of usefull factors. And I'd like to plot a graph like: http://de.wikipedia.org/wiki/Bild:Parallelanalyse.jpg where I don't need the green line (random values). But with str(factanal(data, factors=10)) I cannot figure out where I can find the values for plotting. Can you please help me in this question? Thanks, Martin

...le=TRUE) geopca geopca$CA$eig/geopca$tot.chi summary(geopca, scaling=2) apply(scores(geopca, choices=1.6, display= "species"), + 2,function(x) x/sd(x)) plot(geopca$CA$eig, type= "o", col= "red", xlab= "PCA Axis", ylab= "Variance", main= "Scree plot for the PCA of the Geochem Data") bstick.env<- bstick(19, tot.var=19) #must change number based on number in bstick model bstick.env geopca plot(bstick.env, type="o", lty="dotted", ylim=range(bstick.env, geopca$CA$eig), xlab="PCA Axis", ylab="Iner...

...t and have looked at the partial dependence plots for the different variables effect of the response but I have been looking though the literature to see how people have previously used this type of analysis and I would like to be able to plot out the overall variable importance in some form of PCA Scree graph but havn't got a clue how to even start this so any suggestions will be most appreciated? Many thanks in advance Lara [[alternative HTML version deleted]]

...ta to the NMDS coordinates. I'm fairly new to metaMDS and NMDS in general, so I have what are probably some very basic questions. My fish abundance data consists of 66 sites for which up to 20 species of fish were identified and counted. I ran metaMDS on this data in 3 dimensions (after using a scree plot to check for stress levels in the different dimensions). I then used envfit to correlate a predictor dataset of environmental variables with the NMDS results, using the following code. >Fish<-as.data.frame(read.csv("Fish.csv",header=TRUE, sep = ",")) >Fish.mds<...

After doing a PCA using princomp, how do you view how much each component contributes to variance in the dataset. I'm still quite new to the theory of PCA - I have a little idea about eigenvectors and eigenvalues (these determine the variance explained?). Are the eigenvalues related to loadings in R? Thanks, Paul -- View this message in context:

...Here are my question : - what is the more appropriate function to do so ... I already tried by using the function 'corresp' in the MASS package - it seems to work ... but how is it possible to get all the information concerning the non-centered PCA used by corresp (eigen-values, inertia, scree plot, square cos, ....) In a second step I would like to use hirarchical clustering from the results of the correspondence analysis ... If "Table" is my contingency table (i.e., the number of individuals seen in each case) ... I tried to implment it as follow (for the 2 first component...

...eigenvector, along with the % variance for each eigenvector. This is the best part of the SPSS output. I feel like I'm close to finding the right function in R , but I don't know how to look at the eigenvalues of each component in R. princomp() seems a step in the right direction. 8. Scree plot. No problem, princomp() and screeplot() seem to produce about the right result. 9. Component matrix (lists the variable loading on each factor) factanal() seems to do this, but again the results don't jive with SPSS and I'm unsure why. 10. Factor rotation No problem, factanal(rot...

...help.search('connection') Error in file(file, "r") : All connections are in use > q() Save workspace image? [y/n/c]: y Error in file(file, "wb") : All connections are in use As best as I can tell, I got a bunch of extra connections by experimenting with the split.scree() and layout() functions. But I can't, so far, find a way to remove or close them. When I use ls() to see a list of objects, they all look like things I explicitly created, i.e., vectors, lists, functions, etc., and not like connection objects. I can't find any connection object to clos...

Dear All, I want to know if there is some easy and reliable way to estimate the number of dominant eigenvalues when applying PCA on sample covariance matrix. Assume x-axis is the number of eigenvalues (1, 2, ....,n), and y-axis is the corresponding eigenvalues (a1,a2,..., an) arranged in desceding order. So this x-y plot will be a decreasing curve. Someone mentioned using the elbow (knee)

...is can occasionally give a different result. - prcomp.Rd is changed to reflect the changes to prcomp - summary.prcomp is defined to give a result more like summary.princomp. In Splus summary.prcomp does not exist and the default method is applied, but this difference seems reasonable? - screeplot is made generic - function(...) is changed to function(x, ...) for some plot methods (to be consistent with plot). - print.prcomp is changed to be more like the result from Splus (Splus just uses print.default, so this is slightly different) - plot.prcomp is renamed screeplot.prco...