Thanks, that worked.
Best regards,
Maxim
2016-01-21 22:29 GMT+03:00 Ulrik Stervbo :
>
> You can try facet_grid(variable~., scales = "free_y")
>
> On Thu, 21 Jan 2016 at 19:29 Maxim Fomin wrote:
>>
>> Dear R users,
>>
>> I have a (melted) data fram
, group=variable,
color=variable))+geom_line()+facet_grid(variable~.)
Best regards,
Maxim
P.S dput
structure(list(date = structure(c(3652, 3683, 3712, 3743, 3773,
3804, 3834, 3865, 3896, 3926, 3957, 3987, 4018, 4049, 4077, 4108,
4138, 4169, 4199, 4230, 4261, 4291, 4322, 4352, 4383, 4414, 4442,
4473
2]]
[1] "val2//val3"
[[3]]
[1] "val3"
Above code is the fastest version I was able to come up with (the list
contains about 1 million elements). I guess the for loop can be substituted
by a lapply command making it less complicated
tested with Wald test.
So, my question is follows. How the first test can be performed in R
and where to get variance of state probabilities to perform Wald test
of second hypothesis (I couldn't find relevant data in MSM.lm object)?
Thanks in advance,
Best regards,
Maxim
Dear all,
I am doing business cycle research on industry data. One of methods to identify
cycle is Markov regime switching. As I see, there is a MSwM package
for the purposes which is pretty straightforward to use. However, some
questions for me remain:
1) Are there any packages? This is relevant
ontrast, running the Perl script from within R, it tries to find the
modules in /System/Library/Perl/5.10.0/...
I see that this is not necessarily a pure R question, but as it occurs
specifically using the R system command I thought there might be someone
around here who came across similar proble
y, as it is obviously the size of the grid that make the
problem, as with smaller grid size the first and last axis tick will come
closer to the edges of the plot area!
Right now I'm a bit lost but still I think I might overlook something
pretty simple!
Maxim
[[altern
miss?
I tried in addition lattice's levelplot (no luck yet) as well as a heatmap,
which I find has not enough control to produce more complex pictures
consisting of multiple plots!
Where should I go?
Maxim
[[alternative HTML version deleted]]
___
variable, in
any way I would like to sort for all columns from 1:ncol(x). How to achieve
this?
Best
Maxim
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read th
t optimal) to
depict such data like requested!
For the conventional plot: thanks for the "newline"-trick!
I will play around with the ggplot library and dive a little deeper into the
literature, perhaps I have looked at the wrong papers!
Best
Maxim
2011/8/10 R. Michael Weylandt
value,xaxt="n",beside=T)
Any help is appreciated!
Regards
Maxim
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PLEASE do read the posting guide http://www.R
uot; of the process?
Best
Maxim
2011/3/2
> Don't you expect it to be a lot faster if you cluster 20 items instead of
> 25000?
>
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Maxim
> Sent: Wednesday
hat can I do
to access the levels for the rows?
I guess the solution is easy, but after ours of playing around I thought it
might be a good time to contact the mailing list!
Maxim
[[alternative HTML version deleted]]
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R-help@r-project.org mail
2:ncol(DF)]
}
}
As soon as I set the all directives the script runs forever without any
effect (files sizes: a couple of million lines per file). Is it expected,
that this type of merge takes so much longer (I think it never finishes!)?
Or do I have a conceptual problem with how merge works?
Maxi
Dear All,
I have a short question.
Is there any readily available function that could generate either an ARMAX
model or, more generally, an
AutoRegressive Distributed Lag model?
I am looking for a function that is similar to armaSim() function in fArma
package.
Thank you.
MP
_
t;SD[count]
mean(subtest$val)->Mean[count]
}
cbind(int,Median,SD,Mean)
This works, but: isn't this much too complicated, I bet there is such
functionality embedded in the base packages, but I cannot find it.
Maxim
[[alternative HTML version deleted]]
_
ve, I do not know how to deal with the fact, that many genes
are represented with mutliple probesets, often with different fold changes -
is there a general recipe to deal with this question? Furthermore there are
many probesets with multiple mappings, should these not be excluded from the
analysis?
Great,
works perfect!!!
Thanks a lot
Maxim
2010/1/30 baptiste auguie
> Hi again,
>
> Below are two versions, depending on whether you want to use scan or
> read.table,
>
> ## with scan
> library(reshape)
> listOfFiles <- list.files()
> d <- llply(listOfFi
h code for such a simple task. I'd definitely prefer the plyr solution.
Maxim
2010/1/30 baptiste auguie
> Why don't you post an example of what your input files look like? (to
> the list, not just to me!) A reproducible example is always required
> if you want a good ans
Hi,
I have many files containing one column of data. I like to use the scan
function to parse the data. Next I like to bind to a large vector.
I try this like:
count<-1
files <- list.files() # all files in the working directory
for(i in files) {
tmp <- scan(i)
assign(files[count],
ding
on ID) and then to process it (sorting according to maximum, heatmap)?
Which commands do I have to issue for the manipulation of the data.frame? I
tried the
I'd be glad if someone could help me finding the correct direction to solve
my problem!
Best regards
Maxim
[[a
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