Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down on April 23, and its replacement, is already up and running.

[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

RE: st: cnsreg with singular

From   Cameron McIntosh <>
Subject   RE: st: cnsreg with singular
Date   Tue, 6 Sep 2011 20:57:25 -0400

Hi Demetris,

I wonder if it would also be worthwhile to try some corrective procedures on the design matrix, and see how these compare to the built-in methods in cnsreg?
Yuan, K.-H., & Chan, W. (2008). Structural equation modeling with near singular covariance matrices. Computational Statistics & Data Analysis, 52(10), 4842-4858.   

Yuan, K.H., Wu, R., & Bentler, P.M. (2010). Ridge structural equation modelling with correlation matrices for ordinal and continuous data. British Journal of Mathematical and Statistical Psychology, 64(1), 107–133.

Bentler, P.M., & Yuan, K.-H. (2010). Positive Definiteness via Offdiagonal Scaling of a Symmetric Indefinite Matrix. Psychometrika, 76(1), 119-123.

Highham, N.J. (2002). Computing the nearest correlation matrix - a problem from finance. IMA Journal of Numerical Analysis, 22(3), 329–343.

Knol, D.L., & ten Berge, J.M.F. (1989). Least-squares approximation of an improper correlation matrix by a proper one. Psychometrika, 54, 53–61.

Are you using the model option "col" (keep collinear variables)? Sorry if I am off base given the substantive and methodological nature of your analysis (which I don't know).



> From:
> To:
> Date: Wed, 7 Sep 2011 09:50:35 +1000
> Subject: st: cnsreg with singular
> My question is how does cnsreg deals with a singular matrix?
> Consider the following example:
> . sysuse auto
> . generate mpgrep78 = mpg + rep78
> . regress price mpg rep78 mpgrep78
> Due to perfect collinearity (i.e. a singular design matrix), linear OLS drops one of the explanatory variables.
> But I can force 'estimation' by:
> . constraint 1 mpgrep78 = mpg + rep78
> . cnsreg price mpg rep78 mpgrep78, cons(1)
> This produces estimates for all three explanatory variables. 
> I noticed that the estimates of cnsreg are exactly the same, as taking the estimates of regress and apply the linear relationship to calculate the third parameter. 
> This is what Greene (2010, p.274) suggests as well but in a more elaborate context using multiple regressions. That is, estimate the M-1 parameters and then use the linear relationship to calculate the M parameter. 
> Can someone please confirm whether this is what Stata does too?
> Or does it use some more complex iterative numerical optimisation procedure, perhaps even involving a singular value decomposition?
> I am using Stata/MP2 version 11.2 on Mac.
> many thanks in advance, 
> Demetris
> *
> *   For searches and help try:
> *
> *
> *
*   For searches and help try:

© Copyright 1996–2015 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index