[R] singular factor analysis
spencer.graves at pdf.com
Thu Sep 7 17:49:30 CEST 2006
Hi, Patrick: Thanks very much. I'll try it. Spencer Graves
Patrick Burns wrote:
> This is a very common computation in finance.
> On the public domain page of the Burns Statistics website
> in the financial part is the code and R help file for
> 'factor.model.stat'. Most of the complication of the code
> is to deal with missing values.
> Patrick Burns
> patrick at burns-stat.com
> +44 (0)20 8525 0696
> (home of S Poetry and "A Guide for the Unwilling S User")
> Spencer Graves wrote:
>> Are there any functions available to do a factor analysis with
>> fewer observations than variables? As long as you have more than 3
>> observations, my computations suggest you have enough data to
>> estimate a factor analysis covariance matrix, even though the sample
>> covariance matrix is singular. I tried the naive thing and got an
>> > set.seed(1)
>> > X <- array(rnorm(50), dim=c(5, 10))
>> > factanal(X, factors=1)
>> Error in solve.default(cv) : system is computationally singular:
>> reciprocal condition number = 4.8982e-018
>> I can write a likelihood for a multivariate normal and solve it,
>> but I wondered if there is anything else available that could do this?
>> Spencer Graves
>> R-help at stat.math.ethz.ch mailing list
>> PLEASE do read the posting guide
>> and provide commented, minimal, self-contained, reproducible code.
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