Hi Jordi,
Maybe I misunderstood the usage of that function, but from what I
can see, it's different. princomp.m doesn't provide the kind of output
that I often read about in journal papers; it doesn't explicitly report
weightings for use in a model, % of variance explained by any given
component, or the single component eigenvalue (often used in detailing
usefulness of a component). It also doesn't include the common methods
of limiting the number of PCs to include (Kaiser, MAP, PA). As such, I
feel like this would be best as a separate function. If it would be
best to include these features in princomp.m instead, please advise.
Best,
Kyle
On 01/02/2012 01:36 PM, Jordi Gutiérrez Hermoso wrote:
> On 2 January 2012 11:27, Kyle N Winfree<[email protected]> wrote:
>> The second function performs a principal component
>> analysis akin to that provided by SPSS.
> Were you unaware of this other function when you wrote that?
>
> http://octave.sourceforge.net/statistics/function/princomp.html
>
> - Jordi G. H.
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