similar to: PCA and Regression

Hello, I am trying to see whether there has been a significant difference in whether people experienced damages from wildlife in two different years. I therefore have two columns: year 1: yes no no no yes yes no year 2: no yes no yes I wanted to do a chisq.test, but if I enter it this way: chisq.test(year1, year2) I get the error saying the columns are two different lengths. So then I tried

[cc'ing back to r-help: this is good etiquette so that the responses will be seen by others/ archived for future reference.] On 10-08-25 04:35 PM, Marino Taussig De Bodonia, Agnese wrote: > Yes, I meant "MuMIn" > > the global formula I introduced was: > > rc4.mod<-lm(central$hunting~ central$year + central$gender + central$hunter + central$k.score +

Hi! I had a database with some variables in sequence. Let me say: TX01, TX02, TX03 and TX04. But I need to run some regressions changing the variables... so: variable <- paste("TX0", 1:4, sep="") for(i in 1:4){ test[i] <- lm(variable[i] ~ INCOME, data=database) } But doesn't work... lm tries to find a variable inside database named variable[i] ... Suggestions?

Hi all, R CMD check does not work for me under Windows. This is the error R CMD check mypackage.tar.gz * checking for working latex ... OK tar: and: Not found in archive tar: Settings/miguez/ ... /00_pkg_src: Not found in archive tar: Error exit delayed from previous errors Error: cannot untar mypackage.tar.gz I know tar is available because R CMD build created the tarball in the first place

Dear R users,I have a list of equally structured lists, how can I access e.g. all 2nd compontents in those sub-lists?An example:lst <- list(rep(list(1:3),3), rep(list(4:6),3))> lst[[1]][[1]][[1]][1] 1 2 3[[1]][[2]][1] 1 2 3[[1]][[3]][1] 1 2 3[[2]][[2]][[1]][1] 4 5 6[[2]][[2]][1] 4 5 6[[2]][[3]][1] 4 5 6What I want to get are all second sub-lists, in this case:[[1]][[2]][1] 1 2

Samba 4.8 (Louis debian repo), DM. Today i've had to recovery a deleted file in that share, that use 'vfs_recycle' modules: [Work] comment = Spazio di Lavoro Utente map acl inherit = Yes path = /srv/work read only = No store dos attributes = Yes vfs objects = acl_xattr recycle full_audit volume = Work full_audit:failure = none full_audit:success = mkdir rmdir read pread

Hello, I'm using the "glmulti" package to run models of all the possible combinations of my variables. However, I am only interested in a few interactions between my variables. I have tried the equivalent of: mod1<-lm(y~a+b+c+a:b) glmulti(mod1, level=1) mod2<-lm(y~a+b+c+a:b) glmulti(mod2, level=2) and glmulti("y", c("a", "b", "c"),

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,

Greetings, 1) Is there a nice way of extracting the variance estimates from an lme fit? They don't seem to be part of the lme object. 2) In a series of simulations, I am finding that with ML fitting one of my random effect variances is sometimes being estimated as essentially zero with massive CI instead of the finite value it should have, whilst using REML I get the expected value. I guess

Hai Marco, Can you check this acl and attr are these installed? type acl type attr Or just run : apt-get install -y acl attr Try this : chmod 1770 /srv/work/.cestino/ Which sets : "creator Owner" (1), Owner (7), Group (7), World (0) So the owner and groups can create anything but your enforcing "creator owner" Then set: recycle:subdir_mode = 1700

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-

Hi, The help file on princomp says that 'The signs of the columns of the loadings and scores are arbitrary, and so may differ between differnt programs for PCA, and even between different builds of R'. Does anyone know 1. Whether this applys to all functions like svd, eigen ... etc? 2. During a leave-one-out cross step, I notice the loadings also change sige when a different

I am trying to run PCA on a matrix (the first column and row are headers). There are several cells with NA's. When I run PCA with the following code: ______________________________________ setwd("I:/PCA") AsianProp<-read.csv("Matrix.csv", sep=",", header=T, row.names=1) attach(AsianProp) AsianProp AsianProp.pca<-princomp(AsianProp, na.omit)

Dear R users; Is there any function to plot the confidence ellipse (Hotelling's T^2) in an score plot from a PCA? I have the scores off course , say scores for PC1 and PC2, and the value of the Hotelling's T^2 statistic. Thanks for any hint PM

Hi everybody,   I am doing principal component analysis (PCA) using "prcomp' function. When i did "Biplot", i did not found interesting result and it is based on Principal component (PC) 1 vs PC2. Now, i want to see"Biplot" in combination of either PC1 vs PC3 or PC2 vs PC 3. I did not get the ideas. Does any one have ideas ? I am optimistic on getting some idea.

Hello! I want to do Principal Component Analysis With FactoMiner package in . My data has 923 observation and 12 quantitatives variables. In data frame is there no missing values but are there Zeros as observed values for some units of analysis. When i execute the function >PCA(testeff) is there one error: #error in V* poids: non-numeric argument to binary operator. Can anybody help?

Dear R Helper, I am writing because I seek to perform a varimax rotation on my Principal Components Analysis (PCA) solution. (I have been performing PCA's using the eigen command in R.) If you can tell me how to perform this rotation when I use the eigen command (or the princomp command) I would be thrilled. Thanks so much! Wendy Treynor Ann Arbor, MI USA

Dear all, I have read various descriptions of employing resampling techniques, such as the bootstrap, to estimate the uncertainties of the eigenvectors computed by PCA. When I try

Hi, I was wondering if there is a way of plotting smoothed contours of PCA loadings onto a map. At the moment I have the loadings plotted as positive/negative (red/blue) scaled circles centred around where the physical stations are on a map - but I was wondering if there is a nicer way of plotting this data, perhaps as contours of "regions of influence" or somesuch? Any suggestions

Hi everyone, I'd like to project two pcas onto one device window. I plot my first PCA: biplot(prcomp(t(cerebdevmat)), var.axes=FALSE, cex=c(1,.1), pc.biplot=TRUE) Now I'd like to project the features of another PCA onto this graph. Any suggestions? I know this is easily done in MatLab but haven't figured it out in R. Thanks, Tanya [[alternative HTML version deleted]]