search for: nfactor

...r FrF2 did not work out for Mac OS due to an error in an example that ran without error on all other platforms. I do not find any reason for this. In the past, umlauts or tab characters have sometimes been an issue, but I didn't find any of these. The function definition is FrF2(nruns = NULL, nfactors = NULL, factor.names = if (!is.null(nfactors)) { if (nfactors <= 50) Letters[1:nfactors] else paste("F", 1:nfactors, sep = "")} else NULL, default.levels = c(-1, 1), generators = NULL, resolution = NULL, estimable = NULL, max.nfree2fis = FALSE, randomize = TRUE, seed = NULL,...

...377 -0.01569903 0.03599957   I am pretty troubled by what I see here. So if anyone would offer me some condolence, as well as helpful advice, I am greatly grateful. Thanks a lot. Here are the code and the data.   Thanks a lot.   Wei   nTotal = nMatrix + 1 BuildMod <- function(x){  L1 = matrix(0,nFactor,nFactor)   L1[upper.tri(L1,T)] <- x[1:nMatrix]  return(dlm(   m0  = rep(0,nFactor),   C0  = diag(nFactor)*10,   FF  = matrix(1,1,nFactor),   GG  = diag(nFactor),   V   = tail(x,1)^2,   W   = crossprod(L1),   JFF = matrix(1:4,nr=1),   X   = X   )) } ModFit  <- dlmMLE(Y,rep(0.1,nTotal),BuildMod...

I am running a PCA, but would like to rotate my data and limit the number of factors that are analyzed. I can do this using the "principal" command from the psych package [principal(my.data, nfactors=3,rotate="varimax")], but the issue is that this does not report scores for the Principal Components the way "princomp" does. My question is: Can you get an output of scores using "principal" OR, is there a way to limit the number of factors that are included wh...

...w to do so if I want to use ?principal in 'psych' and any of the GPArotation methods. For example, require(psych) r <- cor(mtcars[,c("am","carb","cyl","disp","drat","gear","hp","mpg")]) pca <- principal(r, nfactors = 8, residuals = T, rotate="none") # or 'varimax' or any other GPArotation supported rotation pca I've turned the 'pca' object and ?principal help page upside down and I still cannot find anything that would resemble a 'scores' value. I'm pretty sure it...

Dear All, In a package, I want to use PCA function. The structure I used follow this page: http://www.statmethods.net/advstats/factor.html. fit<-principle(mydata, nfactors=9, rotation=TRUE) or: result<-PCA(mydata) But I don't known why R language in my computer noticed: "not found principle", "not found PCA". I download and installed R-2.6.2-win32.exe. Thanks alot for answering me. Hue University, VietNam. -- View this mess...

Haj i try to perform a principal component analysis by using a tetrachoric correlation matrix as data input tetra <- tetrachoric (image_na, correct=TRUE) t_matrix <- tetra$rho pca.tetra <- principal(t_matrix, nfactors = 10, n.obs = nrow(image_na), rotate="varimax", scores=TRUE) the problem i have is to compute the individual factor scores from the pca. the code runs perfect if i do not ask for the scores if i ask for the scores i get an error message "Error in scale(x.matrix): object 'x.mat...

...3 1 2 1 1 3 3 1 1 1 1 1 1 3 3 1 2 1 1 3 3 1 1 1 2 3 3 1 2 1 1 3 4 1 1 1 1 3 3 3 3 1 1 1 1 3 4 1 1 1 1 3 3 1 2 1 1 3 3 1 1 1 2 3 3 1 1 1 1 4 4 5 5 6 6 5 6 4 6 4 5 6 5 6 4 5 4 ; run; proc factor data=fact rotate=varimax method=p nfactors=3; var v1-v6; run; /* Output from SAS*/ The FACTOR Procedure Initial Factor Method: Principal Components Prior Communality Estimates: ONE...

...have installed R Factor v2.4.2 This package requires 'polycor' library Unfortunately, 'polycor' does not exist in R3.20 DATASET ACTIVATE DataSet1. *M?rio Basto, Jos? Manuel Pereira, IPCA *Required: SPSS 21 and R Integration Plugin *R Packages required: psych, polycor, GPArotation, nFactors, corpcor, ICS, R.utils. set printback off. Error in library(polycor) : there is no package called 'polycor' This means the very good utility does not run in the way I have installed both R and SPSS Does anyone know what I've done wrong and how to overcome this? Prof. Gavin T L Brown,...

...XXXXXXXXXXXXXXXXXXXXXXX. DATASET NAME DatenSet1 WINDOW=FRONT. DATASET ACTIVATE DatenSet1. SAVE OUTFILE='C:\XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX /COMPRESSED. *M?rio Basto, Jos? Manuel Pereira, IPCA *Required: SPSS 19 and R Integration Plugin *R Packages required: psych, polycor, GPArotation, nFactors, corpcor, ICS. set printback off. -- Till Below (PhD Student) Humboldt-Universit?t zu Berlin

...onses, smooth=TRUE,global=TRUE,polycor=F, ??????????? ML = FALSE,??std.err=FALSE,progress=TRUE) #Regular PCA using stat, psych and FactoMiner, respectively #There is no option for?including the matrix princomp(responses, cor=TRUE) #What kind of correlation is used here? ? principal(r = responses, nfactors = 3, rotate = "Promax") principal(r = W, nfactors = 3, rotate = "Promax") #Do not work PCA(responses, scale.unit=TRUE, ncp=3, graph=T) #How to conduct polychoric principal component analysis using either of #the above package and producing individual and variable factor maps...

...,2] [1,] 1 0 [2,] 1 1 [3,] 4 2 pc=prcomp(gg,center=TRUE,scale=TRUE) # The eigenvectors pc$rotation PC1 PC2 [1,] 0.7071068 0.7071068 [2,] 0.7071068 -0.7071068 # The eigenvalues: > pc$sdev^2 [1] 1.8660254 0.1339746 2. PSYCH Package: > pp=principal(gg,nfactors=2) # The eigenvectors > pp$loadings Loadings: PC1 PC2 [1,] 0.966 -0.259 [2,] 0.966 0.259 # The eigenvalues pp$values 1] 1.8660254 0.1339746 Sincerely, Arlindo [[alternative HTML version deleted]]

...1011 1974 54 58 3 5 1013 1974 65 52 9 24 1001 1975 67 56 1 23 1003 1975 63 55 6 1 1005 1975 60 51 1 47 1007 1975 62 49 7 10 1009 1975 68 50 9 32 1011 1975 55 58 3 5 1013 1975 66 52 9 27"),head=TRUE)) library(psych) pcascores<-principal(pca[,-2], nfactors=1, score=TRUE) However, the scores should be based on the observations per year rather than the full set of observations. The final output should be a data frame with 7 rows (one for each id) and 4 columns (one for each year) filled with the Principal Component Scores per id per year. Any ideas o...

...swers)$r[1:2,1:3] princomp(answers, cor=FALSE)$l[1:2,1:3] eigen(cov(answers))$ve[1:2,1:3] # These 3 lines gives the same result prcomp(answers, center=TRUE, scale=TRUE)$r[1:2,1:3] princomp(answers, cor=TRUE)$l[1:2,1:3] eigen(cor(answers))$ve[1:2,1:3] # This gives another result principal(answers, nfactors=3, rotate="none")$l[1:2,1:3] Furthermore, I tried to use oblimin on the PCA loadings via prcomp and 'principal', but they give different results: # These 2 lines give different results oblimin(prcomp(answers, center=TRUE, scale=TRUE)$r[,1:3])$l[1:2,] principal(answers, nfacto...

...out-of-date version of R. See: ftp://cran.r-project.org/pub/R/src/contrib/Archive/polycor/ Good luck; David. > > DATASET ACTIVATE DataSet1. > *M?rio Basto, Jos? Manuel Pereira, IPCA > *Required: SPSS 21 and R Integration Plugin > *R Packages required: psych, polycor, GPArotation, nFactors, corpcor, ICS, R.utils. > set printback off. > Error in library(polycor) : there is no package called 'polycor' > > This means the very good utility does not run in the way I have installed both R and SPSS > Does anyone know what I've done wrong and how to overcome this...

Hi all: I am trying to do PCA on the following matrix. N1 N2 A1 A2 B1 B2 gene_a 90 110 190 210 290 310 gene_b 190 210 390 410 590 610 gene_c 90 110 110 90 120 80 gene_d 200 100 400 90 600 200 >dataf<-read.table("matrix") >

Thanks to Mr.Liviu Androvic and Mr.Richard Rowe helped me in PCA. Because I have just learn R language in a few day so I have many problem. 1) I don't know why PCA rotation function not run although I try many times. Would you please hepl me and explain how to read the PCA map (both of rotated and unrotated) in a concrete example. 2) Where I can find document relate: Plan S(A), S(A*B),

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

Dear R-List, I have carried out a factor analysis using fa (psych) with nfactors=2, rotation="oblimin" and fm="pa". Now I have to report both pattern AND structure matrix. As I have understood R-Documentation, this can be obtained by setting the "oblique.scores" argument TRUE (structure matrix) or FALSE (pattern matrix), respectively. However bot...

...code is below. Please help. label=data[,"Urban.Rural"] indexU<-which(label=="U") indexR<-which(label=="R") collab<-rep(0,length(data[,1])) collab[indexU]<-"Blue" collab[indexR]<-"Green" library(psych) fit <- principal(mydata, nfactors = num.fac, rotate="varimax", scores = TRUE) z1 <- sum(fit2$loadings[,1]^2) ### need to scale scores and loadings by these factors z2 <- sum(fit2$loadings[,2]^2) biplot(fit$scores[,c(1,2)]/c(z1, z2), loadings(fit)[,c(1,2)]*c(z1, z2), xlabs=rep("", length(collab)), col...

I have an exercise. With 3 kinds of yohourt a,b,c. There are 25 participatients estimate 3 norms: taste (va,vb,vc), structure (ca,cb,cc) and price (ga,gb,gc) and give the mark from 1 to 5. I don't know how to PCA this data. Please help me! I attached the data file follow: Va Vb Vc Ca Cb Cc Ga Gb Gc 4 2 4 5 5 5 4 4 2 2 2 4 3 2 5 4 5 1 2 2 1 2 3 3 3 1 4 1 1 2 2 3 3 4 3 2 3 4 4 4 3 1 2 1 2 1 1 1