similar to: Make factanal accept functions for rotation parameter

--=-hiYzUeWcRJ/+kx41aPIZ Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: 8bit Hi, on March 10 I filed a wishlist bug report asking for the inclusion of some changes to factanal() and the associated print method. The changes were originally proposed by John Fox in 2005; they make print.factanal() display factor correlations if factanal() is called with rotation =

Dear list members, I apologize for putting this (probably) very basic question on the mailing list. I have scanned through the R website (using search) but did not found an answer. (code included below) A factor matrix is simply extracted (which can then subsequently be exported using write.table) by FACT$loadings[1:6,]. I would also like to specifically extract and export

Dear R users: I'm wondering if it's possible to get the residual correlation matrix when using factanal. Since factanal assumes that the errors are normally distributed and independent (provided the factor model fits the data) this would be useful. Of course you would need to submit the data to the function to get the residuals (not just their correlation matrix), but it should be possible

I am performing a large (105 variable) factor analysis with factanal, specifying promax rotation. I kow that some loadings over 1.0 are not unsual with that rotation, but I have some as large as 1.2, which seems extreme. I am skirting the assumptions of the model by using responses on a 7-point rating scale as data; I may have to go back and compute polychoric correlations instead of product

Dear friends, I'm using R to produce the following Factor Analysis: > matriz.cor<-hetcor(matrix(as.factor(data), ncol=variables, byrow=T))$correlations > factanal(x=data, factors=2, covmat=matriz.cor, scores='regression') Then the screen output shows the following message: Error en factanal(x = data, factors = 2, covmat = matrix, : requested scores without

Hi everyone- I have used several methods to calculate principal components rotated using the varimax procedure. This is simple enough. But I would like to calculate the % of variance explained associated with each PC before and after rotation. factanal returns the % of variance explained associated with each PC but I cannot seem to get it to change after rotation. Many thanks for your

Hi, I have a set of covariance matrices but not the original data. I want to carry out some exploratory factor analysis. So, I am trying to construct a covariance matrix list as the input for factanal. I can construct a list which includes the cov, the centers, and the n.obs. But it doesn't work. I get an error that says "Error in sqrt(diag(cv)) : Non-numeric argument to mathematical

In R factanal output, I can't find a function to give me residuals e. I mannually got it by using x -lamda1*f1 -lamda2*f2 - ... -lamdan*fn, but the e I got are not uncorrelated with all the f's. What did I do wrong? Please help. Yijun ____________________________________________________________________________________ Be a better friend, newshound, and

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

Dear list members, Could any expert on factor analysis be so kind to explain how to calculate AIC on the output of factanal. Do I calculate AIC wrong or is factanal$criteria["objective"] not a negative log-likelihood? Best regards Jens Oehlschl?gel The AIC calculated using summary.factanal below don't appear correct to me: n items factors total.df rest.df model.df

Dear all, i wonder if there?s a command to obtain the actual values of a principal component or a factor (not as.factor, but factanal) . test=princomp(USArrests, cor = TRUE) summary(test) just outputs, standard deviation, Prop of Variance and cumulative proportion of variance. test$loadings offers yet another proportion of variance scheme. why is that? Apart from that: Is there a

Hi! I am trying to analyse with R a database that I have previously analysed with SPSS. Steps with SPSS: Factorial analysis Extraction options : I select = Principal component analysis Rotation: varimax Steps with R: I have tried it with varimax function with factanal or with princomp...and the results are different of what I have with SPSS. I think that varimax function is incorporated in

Hello! I have a question about the factanal function. This function returns at the end test statistics like this: Test of the hypothesis that 4 factors are sufficient. The chi square statistic is 4.63 on 2 degrees of freedom. The p-value is 0.0988 Is it possible to get the chi square statistic and the p-value as variables, not the text on the screen? An object of class "factanal"

Dear R-devel list members, Ben Fairbank draw it to my attention that factanal() (in the stats package) doesn't report factor correlations for oblique rotations. Looking at the source, I see that factanal also doesn't save the factor-transformation (rotation) matrix from which these correlations can be computed. I've modified the source, attached below, so that the transformation

Hi R users, I need some help in the followings: I'm doing factor analysis and I need to extract the loading values and the Proportion Var and Cumulative Var values one by one. Here is what I am doing: > fact <- factanal(na.omit(gnome_freq_r2),factors=5); > fact$loadings Loadings: Factor1 Factor2 Factor3 Factor4 Factor5 b1freqr2 0.246 0.486 0.145

Hi, I am currently trying to execute the following command: f<-factanal(factors=k$Components$nparallel,covmat=m,n.obs=2287,rotation="varimax",control=list(opt=list(method=c("BFGS")))) but keep getting the error: L-BFGS-B needs finite values of 'fn' I can't figure out what I am doing wrong here, why isn't optim being told to use BFGS instead of L-BFGS-B...

Hi everyone, I'm running a factor analysis on a correlation matrix with 32 rows and columns. I get the following error when I issue the command sequence mich.fac1 <- factanal(michcor, factor=1) Error in solve.default(cv) : system is computationally singular: reciprocal condition number = 3.24729e-18 I'd really appreciate an explanation for this error and a solution to the problem

Hi. It seems that nearly every time I try to use factanal I get the following response: >faa2db1<-factanal(mretdb1,factors=2,method="mle",control=list(nstart=25)) Error in factanal(mretdb1, factors = 2, method = "mle", control = list(nstart = 25)) : unable to optimize from these starting value(s) > In the case cited above, mretdb1 is synthetic data created

Hi Can anybody please suggest me about the documentation of "factanal.fit.mle()" (Not factanal()------ searching factanal.fit.mle() in R always leads to factanal()). Is there any function for doing principal component factor analysis in R. Regards Souvik Bandyopadhyay JRF, Dept Of Statistics Calcutta University [[alternative HTML version deleted]]

Dear R-help, Using R 1.2.1 on Windows98 to run a factor analysis on a 64x150 matrix of data generated from a simulation model, factanal() reported that it failed to find a solution. Looking at the factanal code, I see the immediate condition that triggered the result: if (best == Inf) stop("Unable to optimize from these starting value(s)") So I am sure factanal() is giving