Thanks in advance. I've used the 'PCA' function from the 'FactoMineR' package to obtain principal component scores. I've tried reading through the package details and similar questions on this foru...

I have a data frame such as follows: x <- c(1, 2, 1, 2) y <- c(1, 2, 3, 4) z <- c(4, 3, 2, 1) df <- data.frame(x, y, z) I am running a factor analysis with the fa funciton from the p...

I am using the psych package's fa command for factor analysis, and so have an object of class fa. I can query the loadings with fac$loadings, but I want to only extract the table containing the loa...

PCA in scikit-learn has an attribute called "explained_variance" which captures the variance explained by each component. I don't see a similar thing like this for FactorAnalysis in scikit-learn. H...

One of the hallmarks of factor analysis is that it allows for non-orthogonal latent variables. In R for example this feature is accessible via the rotation parameter of factanal. Is there any such...

I have a n = 1008 x p = 45 data matrix and I am trying to perform a factor analysis in the data, using the factanal() function. I am getting the same error regardless of the number of factors that ...

I need to perform exploratory factor analysis and calculate scores for each observation using Python assuming that there is only 1 underlying factor. It seems that sklearn.decomposition.FactorAnaly...

In Python I am working on a binary classification problem of Fraud detection on travel insurance. Here is the characteristic about my dataset: Contains 40,000 samples with 20 features. After one ...

I'm trying to perform the following analysis in MATLAB: Direct Oblimin Rotation with a Delta value of 0 and "Kaiser Normalization" I know that MATLAB has a function called rotatefactors...

Im trying to do a factor analysis using R with varimax rotation, but not successful. I run the same exact data on SAS and can get result. in R, if I use fa(r=cor(m1), nfactors=8, fm="ml", rotate=...

I've got an input file with a list of ~50000 clusters and presence of a number of factors in each of them (~10 million entries in total), see a smaller example below: set.seed(1) x = paste("cluste...