similar to: promax (PR#1389)

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

I was wondering whether the following inconsistency of the promax rotation function with the results of a promax rotation using SAS should be considered a bug in the promax function of R. Any comments will be highly appreciated. The following is a loading matrix obtained from a varimax rotation in SAS: # Factor loadings after varimax rotation x <- t(array(c(0.78107, 0.35573,

Hi: How i can make Varimax and Promax Rotation in R 0.63 thanks Jorge M. A. Magalhães -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at

Hi, everyone, This is a little silly, but I cant figure out the algorithm behind lm.fit function used in the context of promax rotation algorithm: The promax function is: promax <- function(x, m = 4) { if(ncol(x) < 2) return(x) dn <- dimnames(x) xx <- varimax(x) x <- xx$loadings Q <- x * abs(x)^(m-1) U <- lm.fit(x, Q)$coefficients d <-

Hi, I found a discrepancy between results in R and Stata for a factor analysis with a promax rotation. For Stata: . *rotate, factor(2) promax* (promax rotation) Rotated Factor Loadings Variable | 1 2 Uniqueness -------------+-------------------------------- pfq_amanag~y | -0.17802 0.64161 0.70698 pfq_bwalk_~ø | 0.72569 0.05570

--=-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 =

Hi, In a discussion of factor analysis in "Using Multivariate Statistics" by Tabachnick and Fidell, two matrices are singled out as important for interpreting an exploratory factor analysis (EFA) with an oblique promax rotation. One is the "structure matrix". The structure matrix contains the correlations between variables and factors. However, these correlations may be

In some documentation for a package I am working on I have > \code{\link[stats]{varimax}} > \code{\link[stats]{promax}} The link to varimax works, but not the one to promax. Promax is an alias under \name{varimax}. This kind of link works within a package, but I'm not sure if it is suppose to work when it is a link to another package. Is this a known limitation or bug, or

Hello I seem to find only two types of rotation for the factanal function in R, the Varimax and Promax, but is it possible to run a orthogonal and oblique rotations in R? Thanks in advance Rosario

# 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

Le 29/11/2017 ? 08:26, Sorin Srbu a ?crit?: > If updated, the instrument software will break, like in an atomic mushroom > cloud, rendering critical hardware non-working and lab people standing > outside my office with torches, pitch-forks and all the shebang. > Yupp, unfortunately that's the current state of some lab equipment > manufacturers that use RHEL as a base...

Hi All, Been having a problem constructing a suitable pattern to represent some vector operations in the DAG. Stuff like andx/orx operations where elements of a vector are anded/ored together. My approach thus far has been to extract the sub elements of the vector and and/or those elements. This is ok for 4 vectors of i32s, but becomes cumbersome for v16i8s. Example instruction: andx $dst

I recently updated my Rannotate application. The interface has been completely redone and there are lots of new features. The basic idea is to create searchable and user annotatable documentation for the Ruby on Rails API (think php.net). Check it out at - http://rails.outertrack.com * What is Rannotate? Rannotate is a Rails application and RDoc YAML generator that work together to provide

To elaborate, it is not only cumbersome writing these patterns for vectors of 16 characters (v16i8), it does not work. When I compile with this pattern for an andx operation on v16i8: /[(set RC:$dst,// // (and (i8 (vector_extract(vt VC:$src), 0 ) ), // // (and (i8 (vector_extract(vt VC:$src), 1 ) ),// // (and (i8 (vector_extract(vt VC:$src), 2 ) ),// ////(and (i8 (vector_extract(vt

Hi, It would be better if you provided the output of dput(dataset).? I am not sure about the structure of your dataset. Just from reading the data as is shown. dat1<- read.table(text=" separator,tissID >,>,2 ,2,1 ,6,5 ,11,13 >,>,4 ,4,9 ,6,2 ,7,3 ,21,1 ,23,58 ,25,9 ,26,4 >,>,11 ,1,12 >,>,21 ,4,1 ,11,3

Is it possible to avoid the loop in the following function (or make the function otherwise more efficient) and can someone point me to a possible solution? (It would be great if hours could be reduced to seconds :-). # --------------------------------------------- RanEigen=function(items=x,cases=y,sample=z) { X=matrix(rnorm(cases*items),nrow=cases,byrow=F) S=crossprod(X-rep(1,cases) %*%

Did anyone else catch the redesign? I don''t know who''s responsible, but it''s lookin better! Good job... -- seth at subimage interactive http://www.subimage.com/sublog/ -------------- next part -------------- An HTML attachment was scrubbed... URL: http://wrath.rubyonrails.org/pipermail/rails/attachments/20060528/f9f92618/attachment.html

Dear All I am using the histogram() function to plot two subsets from my data on the same output display, i.e. there are two histogram plots My code is: histogram( ~ Age | Date, layout = c(1, 2), xlab = "Age (years)", strip = FALSE, strip.left = TRUE, col = "black", border = "white", cex.axis = 1.1, family = "serif", cex.lab =

I'm coming from the scipy community and have been using R on and for the past week or so. I'm still feeling out the language structure, but so far so good. I apologize in advance if I pose any obvious questions, due to my current lack of diction when searching for my issue, or recognizing it if I did see it. Question 1, plots: I have a data frame with 4 type factor columns, also in the

I have a rails 3.rc app that I''m developing. I have a text entry in one my models that can sometimes be quite big. I tried setting :limit => 4294967296 on the text column in my migration file but this doesn''t seem to have any effect. The column is till created as a TEXT column rather than MEDIUMTEXT or LONGTEXT. Does anyone have any idea why this might be happening? Is there