On Wed, 2006-08-16 at 17:01 -0400, John Fox wrote: > Dear Rick, > > It's unclear to me what you mean by constraining "each column of the factor > matrix to sum to one." If you intend to constrain the loadings on each > factor to sum to one, sem() won't do that, since it supports only equality > constraints, not general linear constraints on parameters of the model, but > why such a constraint would be reasonable in the first place escapes me. > More common in confirmatory factor analysis would be to constrain more of > the loadings to zero. Of course, one would do this only if it made > substantive sense in the context of the research. > > Regards, > John > > -------------------------------- > John Fox > Department of Sociology > McMaster University > Hamilton, Ontario > Canada L8S 4M4 > 905-525-9140x23604 > http://socserv.mcmaster.ca/jfox > --------------------------------
I'm trying to build a multivariate receptor model as described by Christensen and Sain (Technometrics, vol 44 (4) pp. 328-337). The model is x_t = Af_t + e_t where A is the matrix of nonnegative source compositions, x_t are the observed pollutant concentrations at time t, and f_t are the unobserved factors. The columns of A are supposed to sum to no more than 100%. They say they are using a latent variable model. If sem can't handle this, do you know of another R package that could? Rick B. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
