I have a function:
call = function()
{
library(rJava)
.jinit(classpath="C:/Documents and Settings/GV/workspace/Test2/bin",
parameters="-Xmx512m")
blah = .jcall("Test2", "D", "sum", 2,2)
return(blah)
}
In java I do re.eval(call()) and I get a value of null. If I run the call
function directly fro
So I have an R function:
function = foo(x)
{
return(x)
}
In java:
I create an Rengine:
Rengine re = new Rengine(args,false,new TextConsole());
int blah = 5
re.eval("foo(blah)");
I get an error(object blah not found). How do I dynamically evaluate my
functions given user input(without hard
I had exactly the same problem with trying to import another .csv file. Turns
out that I was working on a german computer that instead of using a comma
when I saved it as .csv used a semicolon. Just saved it as a normal excel
file, put it on a mates computer and saved it as .csv Worked a treat..
> coeffname <- deparse(substitute(var))
>
> Is that what you wanted?
>
Yes! That gets rid of the extra parameter.
Thanks
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-p
You can get the name of var by doing
coeffname <- deparse(substitute(var))
Is that what you wanted?
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-he
On Oct 16, 2010, at 5:45 PM, Joshua Wiley wrote:
Jim and David,
I certainly agree with your suggestions. How would you implement
all.equal()? Since it compares entire objects (and the OP's goal is
to remove any rows that equal some value), the only option I saw was
to use *apply or a loop.
Multivariate normal distributions with PSD variance matrices occur all the time.
The most common example in practice would probably be the distribution of the
vector of residuals from a normal regression. It has a degenerate distribution
wrt R^n because it is subject to p linear restrictions.
Hello,
from Verzani, simpleR (pdf), p. 80, I created the following function to
test the coefficient of lm() against an arbitrary value.
coeff.test <- function(lm.result, var, coeffname, value) {
# null hypothesis: coeff = value
# alternative hypothesis: coeff != value
es <- resid(lm.result)
You can do this by reading in the image and plotting it, then use the updateusr
function from the TeachingDemos package to set the user coordinates to match
the image (use locator to find the current values of some points). Then you
can just use the locator function to get the coordinates of th
Jim and David,
I certainly agree with your suggestions. How would you implement
all.equal()? Since it compares entire objects (and the OP's goal is
to remove any rows that equal some value), the only option I saw was
to use *apply or a loop. zapsmall() is easier, (though it seems
potentially sl
Dear Spencer,
Thank you for your help. I read your email and that`s the reason why I sent
an email to r-sig-db as you suggested.
But I have just realized that you suggested the command below too. I`ve
tried it and that`s fine. I was waiting to solve my problem to reply the
email to r-help group.
Hi Gary,
On the off chance you want to reduce size to reduce over-plotting, you
can also use semi-transparent colors (otherwise this is completely
irrelevant to you):
# Open and setup new graphics device
dev.new(); exampledev <- dev.cur(); par(mfcol = c(1, 2))
# Regular color
plot(x = Ex <- sampl
Hi:
I'm trying to reproduce an arbitrary precision constant from 'Why and
How to Use Arbitrary Precision' (Ghazi et al., COMPUTING IN SCIENCE &
ENGINEERING May/June 2010;
http://perso.ens-lyon.fr/philippe.theveny/cise.pdf):
d = 173746a + 94228b − 78487c
where: a = sin(1022), b = log(17.1),
Use ?points for more info on changing the appearance of points. The cex
function is what you are looking for.
Chris
On 16 Oct 2010, at 20:12, Hongwei Dong wrote:
Hi, R users,
Can anyone tell me how I can change the size of points in my plot?
For example:
x <- c(1,3,6,9,12)
y <- c(1.5,2,7,8,1
> Ulises M Alvarez
> on Sat, 16 Oct 2010 14:34:25 -0500 writes:
> Hi: I'm trying to reproduce an arbitrary precision
> constant from 'Why and How to Use Arbitrary Precision'
> (Ghazi et al., COMPUTING IN SCIENCE & ENGINEERING May/June
> 2010; http://perso.ens-lyon.fr/p
See also the panel.bpplot function in the Hmisc package. This gives you many
options for extended box plots.
Frank
-
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
View this message in context:
http://r.789695.n4.nabble.com/bwplot-change-whiskers-position-to-percenti
David LeBauer illinois.edu> writes:
>
> Hi,
>
> I would like to write a function that finds parameters of a log-normal
> distribution with a 1-alpha CI of (x_lcl, x_ucl):
>
> However, I don't know how to optimize for the two unknown parameters.
>
Try optim instead.
___
Toby Gass warnercnr.colostate.edu> writes:
> I am working with a dataframe that includes a column, "calendar",
> used for plotting time series.
[snip]
> Is this unavoidable when going back and forth from a .csv, or can I
> do something differently to retain the class?
check out colClasse
Dear helpeRs,
I am working with a dataframe that includes a column, "calendar",
used for plotting time series.
> class(dat$calendar)
[1] "POSIXt" "POSIXlt"
When I finish working, I save my data as a .csv file. When I read
the file in again, "calendar" is always a factor
> class(dat$calendar
On Oct 16, 2010, at 12:12 PM, Hongwei Dong wrote:
Hi, R users,
Can anyone tell me how I can change the size of points in my plot?
For example:
x <- c(1,3,6,9,12)
y <- c(1.5,2,7,8,15)
plot(x,y,pch=20)
How do I reduce the size of those points?
plot(x,y,pch=20, cex=0.2)
plot(x,y,pch=20, cex=
On Sat, Oct 16, 2010 at 10:17 AM, ashz wrote:
>
> Hi,
>
> I have an excel 2007 file located in C:\know and called try.xlsx.
>
> Whan I try to read it I get this error:
>
>> file <- system.file("know", "try.xlsx", package = "xlsx")
>> res <- read.xlsx(file, 2) # read the second sheet
> Error in .j
IRD;
There is a danger in applying logical tests of equality to floating
point numbers. It may be safer to use all.equal or zapsmall in the
construction of your tests.
> all.equal( (2^(0.5))^2 , 2)
[1] TRUE
> (2^(0.5))^2 == 2
[1] FALSE
--
David.
On Oct 16, 2010, at 1:30 PM, Joshua Wiley
Hi, R users,
Can anyone tell me how I can change the size of points in my plot?
For example:
x <- c(1,3,6,9,12)
y <- c(1.5,2,7,8,15)
plot(x,y,pch=20)
How do I reduce the size of those points?
Thanks.
Gary
[[alternative HTML version deleted]]
Hello R Users,
I am trying to do a quadrat count defined by covariate properties in
spatstat. I have read my elevation raster into R (from ascii) and converted
to class "im" for use in spatstat.
Now I have point data of class "ppp" which window is the same extent as the
elevation image. I can conve
try library(RODBC) and odbcConnectExcel2007; it has worked for me.
On Sat, Oct 16, 2010 at 10:17 AM, ashz wrote:
>
> Hi,
>
> I have an excel 2007 file located in C:\know and called try.xlsx.
>
> Whan I try to read it I get this error:
>
>> file <- system.file("know", "try.xlsx", package = "xlsx")
Thank you for the help! I was misunderstanding how 'outer' produced its grid
of values: rather than an application of the supplied function for each
element, the element takes a vector (or list) of values X and Y and combines
them. Of course, looking back, this is the first sentence of the 'deta
It is best to use 'all.equal' keeping in mind FAQ 7.31.
On Sat, Oct 16, 2010 at 1:30 PM, Joshua Wiley wrote:
> Dear IRD,
>
> One way is to select every row except those where y = y.j and then
> assign that to IR. In my example, which() returns a vector of the row
> numbers where the condition ev
On 16/10/2010 2:17 PM, Jonathan Beokhokhei wrote:
Dear friends, please allow me a naive subject oriented question at this moment.
I was wondering whether VCV matrix for some multivariate normal distribution
can be PSD (which I always thought must be PD).
I came across that point as I was worki
Dear friends, please allow me a naive subject oriented question at this moment.
I was wondering whether VCV matrix for some multivariate normal distribution
can be PSD (which I always thought must be PD).
I came across that point as I was working on some sample distribution of some
statistic wh
Hi,
On Sat, Oct 16, 2010 at 9:52 AM, jschamel wrote:
>
> I'm trying to construct an array with output from the application of
> homogeneous input to a bunch of different functions (my final goal is to
> easily analyze running time of a lot of competing functions and summarize
> the results). In
Dear IRD,
One way is to select every row except those where y = y.j and then
assign that to IR. In my example, which() returns a vector of the row
numbers where the condition evaluated TRUE, then I used `-` to select
not those rows.
IR <- IR[-which(IR$y == y.j), ]
HTH,
Josh
On Sat, Oct 16, 20
I'm trying to construct an array with output from the application of
homogeneous input to a bunch of different functions (my final goal is to
easily analyze running time of a lot of competing functions and summarize
the results). In my current iteration, however, only the first function in
the li
dear all
i think i am able to get an unbiased opinion from computing experts
here other than python or perl list.
the question is: which language, perl or python in particular, is
better for data munging (manage and manipulate large-size data /
interact with DB / pre-process data before statistic
Dear All
I have data like this:
> IR
xy
[1,] 5 2.865490
[2,] 3 1.454611
[3,] 3 2.258772
[4,] 6 1.476128
[5,] 4 2.771606
> y.j
y
2.865490
>
and I want to delete data row in IR where y = y.j
How I can do.
IRD
__
R-help@r-project.org
Hi,
I have an excel 2007 file located in C:\know and called try.xlsx.
Whan I try to read it I get this error:
> file <- system.file("know", "try.xlsx", package = "xlsx")
> res <- read.xlsx(file, 2) # read the second sheet
Error in .jnew("java/io/FileInputStream", file) :
java.io.FileNotFo
Version 0.5.2 of the tikzDevice is now available on CRAN in source
form. Binary builds will become available in the next few days. This
build supersedes 0.5.1, which was just released a couple of days ago.
Version 0.5.2 is a recommended upgrade for all users as it contains
fixes a major issue:
Thank you Brian,
Your suggestion helped me a bit but I am not quite there yet. Now I have the
following code:
library(cluster)
library(stats)
D<-matrix(nr=4,nc=4)
rownames(D)<-c("Node 1","Node 2","Node 3","Node 4")
D[1,]<-c(0,.6,.1,.7)
D[2,]<-c(.6,0,.3,.9)
D[3,]<-c(.1,.3,0,.9)
Hi!
Santosh Srinivas wrote:
Dear R-helpers,
Considering that a substantial part of analysis is related data
manipulation, I'm just wondering if I should do the basic data part in a
database server (currently I have the data in .txt file).
For this purpose, I am planning to use MySQL. Is MySQL a
Having managed to reproduce this with the current Rtools212, I needed
tar -zxvf --no-same-owner R-2.12.0.tar.gz
(or -xf: the 'z' is optional, and --no-same-permissions would also be
a useful sanity check).
Although the messages are unclear, they do seem merely to be notices
not errors.
On
I've used the function rq.fit.sfn and rq.fit.panel to estimate a quantile
regression on a panel data set.Now I would like to compute an statistic to
measure the goodness of fit of this model (T-statistics and P-value ).
Does someone know how could I do that?
best wish
--
View this message i
From: Oscar Perpiñan Lamigueiro
Date: October 8, 2010 4:25:34 AM EDT
To: r-packa...@r-project.org
Subject: [R-pkgs] solaR: version 0.20
Hello,
I'd like to announce the availability of the version 0.20 of the
"solaR" package. It provides a set of calculation methods of solar
radiation and perfor
Hi,
Is there any way I can see how exactly the prediction equation is
constructed in the example below? I'd like to be able to replicate the
predictions from the fitted gam object as given by the predict.gam method in
the package "mgcv".
library(mgcv)
data(trees)
ct1 <- gam(Volume ~ s(Height) + s
On 10/16/2010 12:50 AM, Jonas Josefsson wrote:
Hi!
I am trying to produce a graph which shows overlap in latitude for a
number of species.
I have a dataframe which looks as follows
species1,species2,species3,species4.
minlat 6147947,612352,627241,6112791
maxlat 7542842,723423,745329,763492
On 16/10/2010 4:24 AM, Prof Brian Ripley wrote:
The installer (unlike, say, the 2.12.0 RC version) seems to have been
built without 32-bit files (it is too small ... it should be ca 37Mb).
Please try again once Duncan has had a chance to rebuild it.
Thanks for the heads up. Yes, something wen
The download file is about 37mb.
On Sat, Oct 16, 2010 at 4:24 PM, Prof Brian Ripley wrote:
> The installer (unlike, say, the 2.12.0 RC version) seems to have been built
> without 32-bit files (it is too small ... it should be ca 37Mb).
>
> Please try again once Duncan has had a chance to rebuild
On 10/14/2010 06:42 PM, Viechtbauer Wolfgang (STAT) wrote:
> Since the number of parameters then rises linearly with the number of
> subjects, this may be a case where maximum likelihood theory breaks
> down, that is, a Neyman-Scott problem.
My thought too. The basic structure is close to the Rasc
The installer (unlike, say, the 2.12.0 RC version) seems to have been
built without 32-bit files (it is too small ... it should be ca 37Mb).
Please try again once Duncan has had a chance to rebuild it.
On Sat, 16 Oct 2010, Renaud Lancelot wrote:
Dear all,
I've just downloaded R.12.0 from CRA
On 10/16/2010 09:27 AM, Jumlong Vongprasert wrote:
>> predict(lm(x~y),IWJR.complete)
> Error in eval(expr, envir, enclos) : object 'x' not found
>> >
> I'm trying to find answers to solve my problem, but I cann't found what I
> want to solve the problem.
> What do I have to do to solve this proble
Dear all,
I've just downloaded R.12.0 from CRAN
(http://cran.r-project.org/bin/windows/base/release.htm). I am unable
to find RGUI.exe as well as Rterm.exe. Conversely to what is explained
in readme.R.2.12.0:
There are two versions of the R executable in R-2.12.0\bin\i386 (32-bit) or
R-2.12.0\bin
Dear all
I tried to use regression to predicted mu data, but it has error like this:
> IWJR.complete
x y
[1,] 33.17635 2.4705021
[2,] 81.61225 3.3815620
[3,] 65.47392 1.6518975
[4,] 57.97806 1.6110785
[5,] 76.05528 2.1601246
[6,] 41.36090 1.5498132
[7,] 68.77844 2.807869
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