PCA for an unbalanced panel
res = fac_pca_unbal1(Z,meth)
* Z = a (nobs x k) matrix, collecting the variables
* meth = 'stan' if the user wants to perform the analysis on standardized variables
* res = a results tlist, with:
- res('meth') = 'Factor estimation on an unbalanced panel'
- res('y') = the (nobs x k) matrix collecting the variables
- res('standardization') = a boolean, indicating whether variables have been standardized
- res('extrapolated y') = the original panel, with missing values estimated using longitudinal common factor, by means of OLS
- res('loadings') = a (k x 1) vector, collecting the factor loadings
- res('factors') = a (n x 1) vector collecting the longitudinal common factor