wrote:
Sorry forgot to keep the rest of the group in the loop - Luca
-- Forwarded message --
From: Luca Meyer lucam1...@gmail.com
Date: 2015-03-22 16:27 GMT+01:00
Subject: Re: [R] Joining two datasets - recursive procedure?
To: Bert Gunter gunter.ber...@gene.com
Hi
] Joining two datasets - recursive procedure?
To: Bert Gunter gunter.ber...@gene.com
Hi Bert,
That is exactly what I am trying to achieve. Please notice that
negative
v4
values are allowed. I have done a similar task in the past manually by
recursively alterating v4 distribution
Hi Bert, hello R-experts,
I am close to a solution but I still need one hint w.r.t. the following
procedure (available also from
https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0)
rm(list=ls())
# this is (an extract of) the INPUT file I have:
f1 - structure(list(v1 = c(A, A, A, A,
I would have thought that this is straightforward given my previous email...
Just set z to what you want -- e,g, all B values to 29/number of B's,
and all C values to 2.567/number of C's (etc. for more categories).
A slick but sort of cheat way to do this programmatically -- in the
sense that it
Oh, wait a minute ...
You still want the marginals for the other columns to be as originally?
If so, then this is impossible in general as the sum of all the values
must be what they were originally and you cannot therefore choose your
values for V3 arbitrarily.
Or at least, that seems to be
Hi Bert,
Thanks again for your assistance.
Unfortunately when I apply the additional code you suggest I get B=40.23326
C=-8.66603 and not B=29 C=2.56723. Any idea why that might be
happening?
Please see below or on
https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0 the code I
am
...@gmail.com wrote:
Sorry forgot to keep the rest of the group in the loop - Luca
-- Forwarded message --
From: Luca Meyer lucam1...@gmail.com
Date: 2015-03-22 16:27 GMT+01:00
Subject: Re: [R] Joining two datasets - recursive procedure?
To: Bert Gunter gunter.ber...@gene.com
... or cleaner:
z1 - with(f1,v4 + z -ave(z,v1,v2,FUN=mean))
Just for curiosity, was this homework? (in which case I should
probably have not provided you an answer -- that is, assuming that I
HAVE provided an answer).
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
Hi Bert,
Thank you for your message. I am looking into ave() and tapply() as you
suggested but at the same time I have prepared a example of input and
output files, just in case you or someone else would like to make an
attempt to generate a code that goes from input to output.
Please see below
z - rnorm(nrow(f1)) ## or anything you want
z1 - f1$v4 + z - with(f1,ave(z,v1,v2,FUN=mean))
aggregate(v4~v1,f1,sum)
aggregate(z1~v1,f1,sum)
aggregate(v4~v2,f1,sum)
aggregate(z1~v2,f1,sum)
aggregate(v4~v3,f1,sum)
aggregate(z1~v3,f1,sum)
Cheers,
Bert
Bert Gunter
Genentech Nonclinical
Hi Jeff other R-experts,
Thank you for your note. I have tried myself to solve the issue without
success.
Following your suggestion, I am providing a sample of the dataset I am
using below (also downloadble in plain text from
https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0):
1. Still not sure what you mean, but maybe look at ?ave and ?tapply,
for which ave() is a wrapper.
2. You still need to heed the rest of Jeff's advice.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
Data is not information. Information is not knowledge. And
I'm not sure I understand completely what you want to do, but
if the data were frequencies, it sounds like task for fitting a
loglinear model with the model formula
~ V1*V2 + V3
On 3/18/2015 2:17 AM, Luca Meyer wrote:
Hello,
I am facing a quite challenging task (at least to me) and I was
Thanks for you input Michael,
The continuous variable I have measures quantities (down to the 3rd
decimal level) so unfortunately are not frequencies.
Any more specific suggestions on how that could be tackled?
Thanks kind regards,
Luca
===
Michael Friendly wrote:
I'm not sure I understand
I don't understand your description. The standard practice on this list is to
provide a reproducible R example [1] of the kind of data you are working with
(and any code you have tried) to go along with your description. In this case,
that would be two dputs of your input data frames and a dput
Hello,
I am facing a quite challenging task (at least to me) and I was wondering
if someone could advise how R could assist me to speed the task up.
I am dealing with a dataset with 3 discrete variables and one continuous
variable. The discrete variables are:
V1: 8 modalities
V2: 13 modalities
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