Hi all,
This really annoyed since I thought this would be easy with some higher
order function.
Here is what I want:
I have a data frame with two columns, one is ID, another one is Name. I
want to get all rows whose name starts with some specific prefix. I thought
this should be a one-liner inst
Hi John
This was really helpful! Exactly what I needed. Thank you very much - I
really appreciate it!
/Mikael
On Tue, Jan 27, 2015 at 11:54 PM, John C Frain wrote:
> By way of an example, the ox code below reads the sample data.in7 (and
> data.bn7) distributed with the console version of Ox a
Well, the OP already referred to segplot.
But, see, he shouldn't be doing this plot in the first place. Yes, I
know it's fairly standard in science, but it's a bad idea (as are many
others, like the infamous "dynamite plot"). If uncertainty intervals
are desired, they should be model based, obtain
See segplot in the latticeExtra package.
Kevin
On Mon, Jan 26, 2015 at 7:58 PM, Jun Shen wrote:
> Dear list,
>
> I have a couple of lines (superimposed) in an xyplot and just want to add
> error bars to each of the data point. It's been a while since this question
> was asked last time. But the
By way of an example, the ox code below reads the sample data.in7 (and
data.bn7) distributed with the console version of Ox and outputs it as an
Excel file.
#include
#import
main()
{
decl dbase;
dbase = new Database();
dbase.Load("C:\Program Files (x86)\OxMetrics7\ox\data\data.in7");
dbase.Info
Thanks again, Bert, for taking the time to respond to my questions.
It's doing exactly what I want now. I'm fairly new with lattice plots
but they do seem like a big step forward. I'll look for Deepayan's
book; thanks for the tip.
-Tim
On Tue, Jan 2015, 27 at 02:11:33PM -0800, Bert Gunter wrote
1. The trellis.par.get$superpose.line list controls the loess line
appearance, I believe (check this!)
2. To control the overall loess curve in the panel, call it without
the "..." arguments, e.g
panel.loess(x,y, col.line="darkblue")
You may have to modify argument lists appropriately if you wan
Thanks, Bert, for the reply. This is very helpful. I have to admit
I've read the docs for the panel and panel.groups arguments before and
gotten myself pretty confused. Your small example is very helpful.
One more question for the list...
Bert's panel.loess col='darkblue' argument is being ove
Hi,
Not sure if the following is what you look for:
>x <- c(1:10, NA, 12:20)
>sum(x[!is.na(x)])
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Learn to use custom panel functions to give you the flexibility and
features you require.
In this case, you want something like:
xyplot(LRU~PAR|C3C4, groups = species,
panel= function(x,y,...){ ## custom panel function to add an
overall loess line
panel.superpose(x,y,...)
It is a long time since I have used oxmetrics/pcgive files. The data on the
file is in binary form and I do not know of any program that decodes it.
The easiest way to transform the dat would be to find a person who had
access to one of the oxmetrics oxmetrics programs who would read the file
and e
Hello,
I have a dataset consisting of four variables: species (factor, five
levels), C3C4 (factor, two levels), and numeric variables PAR and LRU.
I wish to produce a scatter plot of PAR vs LRU where (1) each species
has a unique symbol and color (2) there is an overlaid loess line that
is calcula
Does the igraph function neighborhood() not do what you need?
B.
On Jan 27, 2015, at 7:22 AM, Manon Lily Ragonnet-cronin
wrote:
> Dear all,
> I am analysis networks using both igraph and network/ sna packages.
> I want to find all the nodes within 3 steps of a specific node but cannot
> fin
Dear all,
I am analysis networks using both igraph and network/ sna packages.
I want to find all the nodes within 3 steps of a specific node but
cannot find a function to do this. I know that kpath.census can
generate tables for the entire network but my network is too large for
this to be a
You might want to look at the examples in error.bars.by in the psych package.
Bill
> On Jan 26, 2015, at 7:58 PM, Jun Shen wrote:
>
> Dear list,
>
> I have a couple of lines (superimposed) in an xyplot and just want to add
> error bars to each of the data point. It's been a while since this
Maybe this is due to the usage of rep() in ifelse():
f.rep <- function(ans){ans <- rep(ans,1);return(ans)}
f <- function(ans){return(ans)}
f(a <- 123) # no print here
f.rep(a <- 123) # prints:
# [1] 123
On 27 January 2015 at 11:54, Bert Gunter wrote:
> Huh??
>
>> ifelse(TRUE, a <- 2L, a <- 3L)
> On Jan 27, 2015, at 6:05 AM, Jorge Fernández García
> wrote:
>
> I need help installing jpeg package. Simple command install.package("jpeg")
> produce the following result. My OS is Fedora 21. Thanks in advance for your
> help.
>
>> install.packages("jpeg")
> Installing package into ‘/home
I need help installing jpeg package. Simple command install.package("jpeg")
produce the following result. My OS is Fedora 21. Thanks in advance for your
help.
> install.packages("jpeg")
Installing package into �/home/cgg/R/x86_64-redhat-linux-gnu-library/3.1�
(as �lib� is unspecified)
trying URL
Thanks!!
On Mon, Jan 26, 2015 at 5:23 PM, peter dalgaard wrote:
>
> > On 26 Jan 2015, at 23:10 , Duncan Murdoch
> wrote:
> >
> > read.table(, colClasses = "character")
> >
> > (You might want "factor" instead of character.)
>
> Or maybe not. I'd expect trouble with getting the levels set to
> c
Huh??
> ifelse(TRUE, a <- 2L, a <- 3L)
[1] 2
> a
[1] 2
Please clarify.
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll
On Mon, Jan 26, 2015 at 2:22 PM, Herv
Hi,
It appears that you want B to be rows 1 thru 4, 6 thru 9, 11 thru 14 and
16 thru 17 from A.
>B <- A[c(1:4, 6:9, 11:14, 16:17),]
>E <- A[16:19,]
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Hi Martin,
On 01/26/2015 04:45 AM, Martin Maechler wrote:
Jim Lemon
on Mon, 26 Jan 2015 11:21:03 +1100 writes:
> Hi Allen, How about this:
> sum_w_NA<-function(x) ifelse(all(is.na(x)),NA,sum(x,na.rm=TRUE))
Excuse, Jim, but that's yet another "horrible misuse of ifelse()"
J
Hi Kathryn,
Selecting the elements of matrix A as you describe is not too difficult:
select_A<-function(A,B) {
thisA<-A[A[,1] == B$p[1],]
newmat<-matrix(c(rep(p[1],B$nq[1]),rep(thisA[,2],length.out=B$nq[1])),ncol=2)
for(i in 2:dim(B)[1]) {
thisA<-A[A[,1] == B$p[i],]
newmat<-
rbind(newmat
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