c2.load.all<-cbind(period,pc1.load.all)
# and plot loadings for each each variable vs. the period...
Ignacio
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Laura Quinn
Sent: Monday, May 16, 2005 4:34 AM
To: Gavin Simpson
Cc: r-help@stat.math.
Laura Quinn <[EMAIL PROTECTED]> wrote:
>I am wishing to investigate the temporal evolution of the pca: if we
>assume that every 50 rows of my data frame is representitive of, for
>instance, 1 day of data, I am hoping to automate a process whereby a pca
>is performed on every 50 rows of data and the
hi all ... again
I'm sorry ... my answer doesn't deal with the subject.
off-topic ;(
Pierre
At 10:33 16/05/2005 +0100, Laura Quinn wrote:
>Sorry, I don't think I made myself clear enough with my initial query!
>
>I am wishing to investigate the temporal evolution of the pca: if we
>assume that
Laura Quinn wrote:
Sorry, I don't think I made myself clear enough with my initial query!
I am wishing to investigate the temporal evolution of the pca: if we
assume that every 50 rows of my data frame is representitive of, for
instance, 1 day of data, I am hoping to automate a process whereby a pc
Hi all,
You can use the sepan function in the library ade4.
Maybe it's a bit difficult but it provides interesting perspectives.
This function uses arguments 'ktab' (K-table) which correspond to a list of
data frames with the same row.names in common.
?ktab
# example : two propoistions
data(meau
Sorry, I don't think I made myself clear enough with my initial query!
I am wishing to investigate the temporal evolution of the pca: if we
assume that every 50 rows of my data frame is representitive of, for
instance, 1 day of data, I am hoping to automate a process whereby a pca
is performed on
Laura Quinn wrote:
Please could someone point me in the right direction as I appear to be
having a total mental block with fairly basic PCA problem!
I have a large dataframe where rows represent independent
observations and columns are variables. I am wanting to perform PCA
sequentially on blocks o
