similar to: "Unable to optimize" error returned in factanal using R-3.0.1, Windows 64 bit, and OpenBLAS

Dear all, The 'make check' step fails for the pacakge mva on IBM AIX. The tail of the Rout log file looks like: > for(factors in 2:4) print(update(Harman23.FA, factors = factors)) Call: factanal(factors = factors, covmat = Harman23.cor) Uniquenesses: height arm.span forearm lower.leg weight 0.170 0.107 0.166

--=-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 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, I have obtained some results with factanal that seem to support a hypothesis I already had, and I'd like to verify that I can indeed conclude this from this new analysis. We had subjects reproduce perceived trajectories with a device that allowed us to measure spatial position (the path) and the device's orientation at any of those positions. From this, we calculated the rotation of

Full_Name: Madeleine Yeh Version: 1.9.1 OS: AIX 5.2 Submission from: (NULL) (151.121.225.1) After compiling R-1.9.1 on AIX 5.2 using the IBM cc compiler, I ran the checks. One of them failed. Here is the output from running the check solo. root@svweb:/fsapps/test/build/R/1.9.1/R-1.9.1/tests/Examples: ># ../../bin/R --vanilla < stats-Ex.R R : Copyright 2004, The R

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

# I have a question about how factanal is calculating the regression factor # scores based on an oblique rotation (promax) of the factors. # # As is explained in the help file, regression factor scores are # obtained as # # hat f = Lambda' Sigma^-1 x # # However, according to Harman's "Modern Factor Analysis" (e.g. second # edition, pp. 351-352) the formula is # # hat f = Phi

Hi, I wonder why factor scores produced by factanal are correlated, and I'd appreciate any hints from people that may help me to get a deeper understanding why that's the case. By the way: I'm a psychologist used to SPSS, so that question my sound a little silly to your ears. Here's my minimal example: *********************************************** v1 <-

Dear developers, I just noticed that step() function currently prints the current model using message(), but the resulting model using print(). The relevant commands within the step() body are: if (trace) message("Start: AIC=", format(round(bAIC, 2)), "\n", cut.string(deparse(as.vector(formula(fit)))), "\n") (with example() output:) Start: AIC=190.69

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

I wanted to test if there exists already a name (which is incidentally a substring of another name) in a dataframe. I did e.g.: > data(swiss) > names(swiss) [1] "Fertility" "Agriculture" "Examination" "Education" [5] "Catholic" "Infant.Mortality" > ! is.null(swiss$EduX) [1] FALSE > !

Hi All, Can someone help me?The way to do this may be very easy but i do not know. *Question1:----* factanal() function produces the results in this way:-- *RESULTS:--* *>fact1<- factanal(data_withNA,factors=1,rotation="none") >fact1$"loadings"* Loadings: Factor1 i1 0.784 i2 0.874 i3 0.786 i4 0.839 i5 0.778 i6 0.859 i7 0.850 i8 0.763 i9 0.810 i10 0.575

hello, I'd like know how to sort a data frame in R for example how I should do to sort by Catholic with swiss data frame like below thanks Fertility Agriculture Examination Education Catholic Infant.Mortality Courtelary 80.2 17.0 15 12 9.96 22.2 Delemont 83.1 45.1 6 9 84.84 22.2

Dear Users, I ran factor analysis using R and SAS. However, I had different outputs from R and SAS. Why they provide different outputs? Especially, the factor loadings are different. I did real dataset(n=264), however, I had an extremely different from R and SAS. Why this things happened? Which software is correct on? Thanks in advance, - TY #R code with example data # A little

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

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

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, I have found a minor problem with leaps(). In 1.3.1 under Windows 2000 I seem to only be able to obtain values for one statistic at a time. That is choosing method=c("Cp","adjr2","r2") just gives Cp values. To mimic the output of Minitab's MTB > BReg 'Fertility' 'Agriculture'-'Infant.Mortality' ; SUBC> NVars 1 5; SUBC>

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]]