Here is a toy example of what I want
library(lattice)
result <- data.frame(score = 1:10, theta = seq(from = -5, to = 5, length = 10))
result$theta2 <- result$theta + .3
xyplot(score ~ theta + theta2, result, type = c('g', 'l'))
However, in reality, the number of variables along the x-axis will v
Hello,
I am trying to create a data set from an object called ‘anno’ in my
environment. I’ve tried arguments like saveRDS(anno, file = “”) and
save(anno, file “.RData”) to save the object as a file to see if that will
work, but it seems for the particular procedure I am trying to carry out, I
ne
Hi Spencer,
Your description doesn't make any sense to me. If anno is already an R
object, what are you trying to do with it?
data() is for loading datasets that come with packages; if your object
is already an R object in your environment, then there's no need for
it.
It sounds like you are pos
Sarah,
I am trying to extract phenoData (ie sample information) from the object
as part of a procedure to analyze my array for probe sets, which I realize
is under the BioConducter package Biobase and not relevant to this mailing
list.
Yes the original procedure uses data from the Dilution da
xyplot(formula(result), result, type = c( 'g','l'))
See ?formula (the part about the dataframe method) for details.
Bert Gunter
"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
Right. If you have some equivalent to the Dilution dataset, then you
need to get it into R in the appropriate way for whatever data you
have.
data() is merely a way to get stored R data into your R session.
There's no reason you need to use data() rather than read.table() or
whatever is appropriat
Sarah,
Thank you for the reference to ?data. Upon further research into the
matter, I think I can provide a simpler explanation than the one previously
provided. I am trying to reproduce the following code with an object --
'anno' -- in my data frame/environment.
>fake.data <- matrix(rnorm(8*20
You don't need fake.data or rnorm(), which was used to generate the fake data.
You need to use your real data for the analysis, not anything randomly
generated for example purposes, or anything included with a package
for example purposes.
In both cases, those are just worked examples.You need to
Okay. I am a little confused as to how to proceed with that. The next part
of the procedure as seen below appears to be substituting information from
this fake data set into the following arguments in order to
sample.info <- data.frame( + spl=paste('A', 1:8, sep=''), +
stat=rep(c('cancer' , 'heal
Sarah,
Okay. I am a little confused about how to proceed. How do I substitute my
anno object for the Dilution dataset, when in these following lines of the
code, as it appears that info from the fake dataset was extracted.. ?
sample.info <- data.frame( + spl=paste('A', 1:8, sep=''), +
stat=rep(
Okay, at this point I have three suggestions, because you're clearly
not yet understanding the R workflow.
1. Read at least the Intro to R manual.
https://cran.r-project.org/doc/manuals/R-intro.pdf
2. Go through your sample code carefully, step by step, using
functions like str() and head() to loo
Thank you for the advice
On Fri, Jul 19, 2019 at 2:25 PM Sarah Goslee wrote:
> Okay, at this point I have three suggestions, because you're clearly
> not yet understanding the R workflow.
>
> 1. Read at least the Intro to R manual.
> https://cran.r-project.org/doc/manuals/R-intro.pdf
> 2. Go thr
Hello all,
The R code below tests if values of the variable �t� are included or not within
intervals that are defined from the data frame dat. The expected results are
displayed using the function "rle" (see code below). Here is the code:
ta <- 100
tb <- 140
tc <- 40
td <- 85
datF <- data.fram
If I understand correctly (make sure that I do!), ?findInterval should
essentially do what you want.
In your example (thanks!), I assume that:
1) The cutpoints defining your intervals are increasing, so p1 < p2 < p3
(p4 is unused)
2) You want to know which t2's are in the two intervals t2 <= p1 a
Thank you very much Bert for your answer. I would like reproduce the same
results as the code below:
ta <- 100
tb <- 140
tc <- 40
td <- 85
datF <- data.frame(t = 1:3650, e = NA)
dat <- data.frame(a = seq(1, 3650, 365),
b = seq(ta, 3650, 365),
c = seq(ta + 1, 3
There is no reason for you to tell anyone on this list how they should
accomplish your goal... we are not a free (or paid) programming service.
If you are in fact obligated to use your proposed approach, then you are most
likely doing homework and this list is expressly not for homework (re-rea
Dear R users,
I am interested in estimating the effects of a treatment on two
time-to-event traits (on simulated data), accounting for the dependency
between the two time-to-event outcomes.
I precise that the events are NOT recurrent, NOT competitive, NOT ordered.
The individuals are NOT related
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