Re: [R] singular factor analysis

From: Spencer Graves <spencer.graves_at_pdf.com>
Date: Thu 07 Sep 2006 - 15:49:30 GMT

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@burns-stat.com
> +44 (0)20 8525 0696
> http://www.burns-stat.com
> (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
>> error:
>> > 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?
>> Thanks,
>> Spencer Graves
>>
>> ______________________________________________
>> 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.
>>
>>
>>
>>



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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 Sep 08 03:20:23 2006

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