similar to: prcomp: where do sdev values come from?

Hello, It might be a trivial question but I just wanted to find out the relationship between sdev and proportion of variance generated by prcomp. I got the following result from my data set ???????????????????????????? PC1????? PC2????? PC3 Standard deviation???? 104.89454 15.40910 9.012047 Proportion of Variance?? 0.52344? 0.01130 0.003860 Cumulative Proportion??? 0.52344? 0.53474 0.538600

Dear all, I have a question about the 'sdev' value returned by the princomp function (which does principal components analysis). On the help page for princomp it says 'sdev' is 'the standard deviations of the principal components'. However, when I calculate the principal components for the USArrests data set, I don't find this to be the case: Here is how I

Hi everyone, I wonder if anyone knows the reason why the outputs of the same reprojection in r and arcgis are different?. The magnitude of the change can be up to 40 km in the poles. Basically, I have a database of points equally separated by one degree over the globe. In ARCGIS, I am projecting the data in GCS-WGS-1984 and then reprojected it to Berhmann to ensure equal area

> Date: Wed, 30 Jun 1999 11:12:24 +0200 (MET DST) > From: Torsten Hothorn <hothorn at amadeus.statistik.uni-dortmund.de> > > yesterday I had a little shock using qr (or lm). having a matrix > > X <- cbind(1,diag(3)) > y <- 1:3 > > the qr.coef returns one NA (because X is singular). So I computed the > Moore-Penrose inverse of X (just from the

Saludos, estoy intentando usar la función reprojectHDF() ( http://r-gis.net/?q=ModisDownload). #### source('ModisDownload.R') library(raster) library(RCurl) path<-"~/R/MODIS/Data/Test" input<-list.files(path,"*.hdf",all.files=T,recursive=T,full.names=T) input outname<-paste(substr(input[1],40,45),".tif",sep='') outname

I'm only now realizing that we have severe problems with R on our AMD 'Opteron' and 'Athlon64' clients running Redhat Enterprise with all 64-bit libraries (AFAICS). The Lapack problem happens for R-patched and R-devel both on the Opteron and the Athlon64. Here are platform details: o "gcc -v" and "g77 -v" both end with the line gcc version 3.2.3

Hi, I need to find the z-score of the data present in a speardsheet. The values needs to be calculated for each gene across the samples (refer the example). And, it should be a simple thing, but I am unable to do it right now ! The example re the structure of the spreadsheet is - # Example: MyFile <- read.csv( text= "Names,'Sample_1','Sample_2','Sample_3'

Dear all, I have a problem with interactions in lmer. I have 2 factors (garden and gebiet) which interact, plus one other variable (home), dataframe arr. When I put: / lmer (biomass ~ home + garden:gebiet + ( 1|Block), data = arr)/ it writes: /Error in lme4::lFormula(formula = biomass ~ home + garden:gebiet + (1 | : rank of X = 28 < ncol(X) = 30/ In the lmer help I found out that if not

Hello all, I have the square symetric matrix A: 2 1 1 1 2 1 1 1 2 My first question is what is the easiest way to enter this matriz in R? Second, matrix A has an eigenvalue with multiplicity 2, in this case, how could I find the two related ortogonal eigenvectors given below by R, without the help of R, I mean, I want to know how R calculate this eigenvectors related to the same eigenvalue.

Hi all, We followed some books and sample codes and did some EMM estimation, only to find it won't be able to generate forecast. This is because in the stochastic volatility models we are estimating, the volatilities are latent variables, and we want to forecast 1-step ahead or h-step ahead volatilities. So it is nice to have the system estimated, but we couldn't get it to forecast at

Hi dear R-users I try to reproduce the steps included in a LDA. Concerning the eigenvectors there is a difference to SPSS. In my textbook (Bortz) it says, that the matrix with the eigenvectors V usually are not normalized to the length of 1, but in the way that the following holds (SPSS does the same thing): t(Vstar)%*%Derror%*%Vstar = I where Vstar are the normalized eigenvectors. Derror

> > Hi, > > I used > GDALinfo("MOD13Q1.A2001049.h13v11.005.2007002215512.250m_16_days_EVI.tif") and > got the results: > > rows 10 > columns 11 > bands 1 > origin.x 150701.4 > origin.y 7744897 > res.x 250 > res.y 250 > ysign -1 > oblique.x 0 > oblique.y 0 > driver GTiff >

Hello list I have been given some Excel sheets with data laid like this: Col1 Col2 A 3 2 3 B 4 5 4 C 1 4 3 I was hoping to import this into R as a csv and then get the mean and SD for each letter in column 1. Could someone give me some guidance on best to approach this? Thanks Iain

HI Greg, Sorry, I misunderstand your question. I am not sure whether it works with numSummary() from library(Rcmdr). You could use other ways, such as: test<-read.table(text=" ?id year incidents ?100??? 1??????? 0 ?101??? 1??????? 1 ?102??? 1??????? 21 ?100??? 1??????? 27 ?101??? 1??????? 3 ?102??? 1??????? 12 ?100??? 2??????? 5 ?101??? 2??????? 5 ?102??? 2??????? 19 ?100??? 2??????? 10