Erm, Jim I am loading in the affyPLM package first (when needed) and this
was a question based on loading/saving R objects. PLMset was an example.
Many thanks,
Quin
-Original Message-
From: James W. MacDonald [mailto:[EMAIL PROTECTED]
Sent: 31 July 2007 14:54
To: Quin Wills
Cc: r-help
2007 23:51
To: Quin Wills
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] problems saving and loading (PLMset) objects
you just need to say:
load("expr.RData")
You should not be assigning it to 'expr' since it is already 'load'ed
On 7/30/07, Quin Wills <[EMAIL PROT
Hi
I'm running the latest R on a presumably up to date Linux server.
'Doing something silly I'm sure, but can't see why my saved PLMset objects
come out all wrong. To use an example:
Setting up an example PLMset (I have the same problem no matter what example
I use)
> library(affyPLM)
Excellent! Thanks.
-Original Message-
From: Dimitris Rizopoulos [mailto:[EMAIL PROTECTED]
Sent: 17 July 2007 13:40
To: Quin Wills
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] multiple rugs on a single plot
you could use different colours, e.g.,
x1 <- rnorm(100, -2.5, 1)
x2 <-
Hi
I could only find some discussion on this wrt lattice graphics (which I'm
not using). Apologies if I'm missing something obvious.
I'd like to produce 3 rug plots under a kernel density plot for a
population. The population is subdivided into 3 subpopulations, which I'd
like the rug plot
Thank you... I will definitely check that up.
Quin
-Original Message-
From: Stéphane Dray [mailto:[EMAIL PROTECTED]
Sent: 27 July 2006 09:04 AM
To: Quin Wills
Cc: 'Berton Gunter'; r-help@stat.math.ethz.ch
Subject: Re: [R] PCA with not non-negative definite covariance
As said
EMAIL PROTECTED]
Sent: 26 July 2006 05:10 PM
To: 'Quin Wills'; [EMAIL PROTECTED]
Cc: r-help@stat.math.ethz.ch
Subject: RE: [R] PCA with not non-negative definite covariance
Not sure what "completely analagous" means; mds is nonlinear, PCA is linear.
In any case, the bottom line i
a
pairwise basis when calculating the distances.
Quin
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
Sent: 25 July 2006 09:24 AM
To: Quin Wills
Cc: r-help@stat.math.ethz.ch
Subject: Re: [R] PCA with not non-negative definite covariance
Hi , hi all,
> Am I correct
Am I correct to understand from the previous discussions on this topic (a
few years back) that if I have a matrix with missing values my PCA options
seem dismal if:
(1) I dont want to impute the missing values.
(2) I dont want to completely remove cases with missing values.
(3)
Hi,
What is the best general strategy to prevent returned errors from
interrupting whatever it is I am running? Only by using options()?
This is a problem for me in 2 particular cases:
(i) An error breaking my loops.
(ii) I would like to run some regressi
Are there functions to weight variables for clustering in R? I can't seem to
find anything, so apologies if there is.
I am particularly interested in weighting variables (starting with kmeans)
to optimise inter/intra-cluster distances. It seems to me that if certain
variables do show a strong c
-
From: Prof Brian Ripley [mailto:[EMAIL PROTECTED]
Sent: 03 May 2006 10:33
To: Quin Wills
Cc: 'Uwe Ligges'; r-help@stat.math.ethz.ch
Subject: Re: [R] How to use a validation set rather than the default
cross-validation in rpart() ?
On Wed, 3 May 2006, Quin Wills wrote:
> Many thanks.
Many thanks. I'm using it for pruning and was hoping that rpart allows use
of a validation set rather than cross-validation for generating a CP/error
table.
-Original Message-
From: Uwe Ligges [mailto:[EMAIL PROTECTED]
Sent: 03 May 2006 07:53
To: Quin Wills
Cc: r-help@stat.math.et
I want use a validation set for my classification tree rather than the
default 10-fold validation in rpart() but can't see which arguments to use
to get this right. Advice appreciated thanks. I assume that this is
possible!
[[alternative HTML version deleted]]
__
Thank you all, this has been a great help (including the methodological
advice). Very interesting - I'll be sure to read the lecture.
Quin
-Original Message-
From: Liaw, Andy [mailto:[EMAIL PROTECTED]
Sent: 22 February 2006 01:18
To: 'Brian S Cade'; [EMAIL PROTECTED]
Cc
I am using "nls" to fit dose-response curves but am not sure how to approach
more robust regression in R to get around the problem of the my error
showing increased variance with increasing dose.
My understanding is that "rlm" or "lqs" would not be a good idea here.
'Fairly new to regression
The question is general for all functions, but here is a specific example -
# For the logistic regression of the following correlated variables:
C <- c(457, 1371, 4113, 12339, 37017, 111051, 333153, 999459)
E <- c(0.003858377, 0.014334578, 0.014092836, 0.737950754, 0.996371828,
0.997482
#x27;t good. Is this the configure file I find in SJava?
Do I need to move it somewhere for this to work?
All of the best,
Quin
-Original Message-
From: Duncan Temple Lang [mailto:[EMAIL PROTECTED]
Sent: 27 July 2005 09:30 PM
To: Quin Wills
Subject: Re: [R] Installing SJava (I'm
Hi. Day three and Im still struggling with this. Any advice to overcome the
final hurdle will be enormously appreciated. I now have all the right Java
applications etc. in their right places and have managed to get rid of most
errors but still get this:
Making package SJava
Building J
I am not a techie and have been struggling 2 days solid to try and install
SJava (the source from http://www.omegahat.org/RSJava/). Does anybody have a
binary file for me (I am Windows XP and rw2001)? I have tried installing
Perl, mingwin and the cygwin tools but still no luck. When I try R CMD
IN
Apologies, I am a non-techie so am finding installing SJava (which I need
for RMAGEML) very frustrating indeed.
I am running rw2001 on WindowsXP with Java - jre1.5.0_02. Could somebody
please explain to me step-by-step how to install it as I have tried all the
help files. The websites (HYPERL
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