From: Rick Bilonick <rab_at_nauticom.net>

Date: Thu 17 Aug 2006 - 22:06:52 EST

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. Received on Fri Aug 18 01:34:28 2006

Date: Thu 17 Aug 2006 - 22:06:52 EST

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.

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