Hilfe
Subject: Re: [R] PCA with NA
Hello,
unfortunately I can not find the pcaMethods package.
Birgit
Am 26.11.2007 um 16:26 schrieb Kevin Wright:
> The pcaMethods package offers a collection of different algorithms for
> PCA, some of which (NIPALS and others) can be used on data that hav
Hello,
unfortunately I can not find the pcaMethods package.
Birgit
Am 26.11.2007 um 16:26 schrieb Kevin Wright:
> The pcaMethods package offers a collection of different algorithms for
> PCA, some of which (NIPALS and others) can be used on data that have
> missing values.
>
> Kevin Wright
>
>
The pcaMethods package offers a collection of different algorithms for
PCA, some of which (NIPALS and others) can be used on data that have
missing values.
Kevin Wright
On Nov 24, 2007 4:59 PM, Hartmut Oldenbürger <[EMAIL PROTECTED]> wrote:
> Hi Birgit, and All
>
> Possibly you should not consid
Hi Birgit, and All
Possibly you should not consider the case completed ;-)
There is an important alternative to imputing means, or estimates from
first or second order
regression (Frane, Psychometrica, BMDP): partial-least-squares (Wold),
which uses as much
information from the data as possible t
Thanks to all for your help.
Only to complete this:
The NA´s in my case mean that I have no information for this
character in this species. These are not ecological data, so I have
to deal somehow with the NA´s without replacing by zero.
I think Thibauts help is very useful.
Thanks a lot
B
The 'factor.model.stat' function (available in the public
domain area of http://www.burns-stat.com) fits a principal
components factor model to data that can have NAs.
You might be able to copy what it does for your purposes.
It does depend on there being some variables (columns)
that have no missi
Birgit Lemcke wrote:
>Dear all,
>(Mac OS X 10.4.11, R 2.6.0)
>I have a quantitative dataset with a lot of Na´s in it. So many, that
>it is not possible to delete all rows with NA´s and also not
>possible, to delete all variables with NA´s.
>Is there a function for a principal component analysi
Dear Birgit,
You need to think about why you have that many NA's. In case of vegetation
data, it is very common to have only a few species present in a site. So how
would you record the abundance of a species that is absent? NA or 0 (zero)? One
could argument that it needs to be NA because you
8 matches
Mail list logo